diff --git a/RandomEFT/RandomEFT/Makefile b/RandomEFT/RandomEFT/Makefile
deleted file mode 100644
index 671a392..0000000
--- a/RandomEFT/RandomEFT/Makefile
+++ /dev/null
@@ -1,5 +0,0 @@
-# Simple makefile
-testRamdom: testRandom.cxx
-	g++ -c -fPIC Root/*.cxx -I. `root-config --cflags`
-	g++ -c -fPIC cMorphWrapper.cxx -I. `root-config --cflags`
-	g++ -shared -Wl,-soname,libcMorphWrapper.so -o libcMorphWrapper.so *.o `root-config --glibs`
diff --git a/RandomEFT/RandomEFT/cMorphWrapper.cxx b/RandomEFT/RandomEFT/cMorphWrapper.cxx
deleted file mode 100644
index 83b6765..0000000
--- a/RandomEFT/RandomEFT/cMorphWrapper.cxx
+++ /dev/null
@@ -1,203 +0,0 @@
-/**
- * Basic Wrapper for EFT Morphing code
- *
- *
- */
-
-#include "RandomEFT/EFTCrossSection.h" 
-#include "RandomEFT/EFTMorphing.h" 
-#include "TH1F.h"
-#include "TFile.h"
-#include "TGraph.h"
-#include <iostream> 
-#include <string>
-#include <sstream>
-#include <iomanip>
- 
-using namespace std;
-
-// Simple EF TMorphing wrapper code for coupling 
-// and cross section computation
-class MorphWrapper{
-public:
-  MorphWrapper(){ weights = new float[nsamples]; };
-  ~MorphWrapper(){ delete weights; };
-  void setSampleData(const char *in_data);
-  float * getWeights();
-  const char * getCrossSections();
-  void printData();
-
-private:
-  int ncouplings;
-  int nsamples;
-  vector<float> morphed;
-  vector<string> types;
-  vector<vector<float> > prod;
-  vector<vector<float> > dec;
-  vector<vector<float> > same;
-  vector<vector<float> > samples;
-  float *weights;
-};
-
-void MorphWrapper::setSampleData(const char *in_data){
-  // Resetting old data in case is being called again
-  morphed.clear(); types.clear(); prod.clear(); dec.clear(); same.clear(); samples.clear(); 
-
-  string data_string(in_data,strlen(in_data));
-  //cout << in_data << endl;
-
-  stringstream ss(data_string);
-  // read n samles and ncouplings
-  ss >> nsamples >> ncouplings;
-
-  // read types from string for each coupling
-  string type;
-  for (int i = 0; i < ncouplings; i++){
-    ss >> type;
-    types.push_back(type);
-  }
-
-  // reading target sample
-  float target;
-  for (int i = 0; i < ncouplings; i++){
-    ss >> target;
-    morphed.push_back(target);
-  }
-
-  // reading each sample
-
-  float sample_coupling;
-  for (int i = 0; i < nsamples; i++){
-    samples.push_back(vector<float>());
-    for (int j = 0; j < ncouplings;j++){
-      ss >> sample_coupling;
-      samples[i].push_back(sample_coupling);
-    }
-  }
-  //cout<<"Basis samples "<<endl;
-  //calculating N eff for this basis.   
-  // making vectors of couplings for this basis
-  for(unsigned int i  = 0; i<nsamples; ++i)
-  {
-    vector<float> s = samples[i];
-
-    vector<float>  prod_l;
-    vector<float>  dec_l; 
-    vector<float>  same_l; 
-
-    //cout<<endl;
-
-    //cout<<"{";
-    for (unsigned int j  = 0; j<ncouplings; ++j)
-    {
-      //cout<< s[j];
-      //if(j<(ncouplings-1)) cout<<"," << " ";
-      if(types[j] == "P")      prod_l.push_back(s[j]);
-      else if(types[j] == "D") dec_l.push_back(s[j]);
-      else if(types[j] == "S") same_l.push_back(s[j]);
-      else{
-        cout<<"Unknown coupling type"<<endl;
-
-      }//end of the type selection loop                                                                                                                                      
-    }//end of sample couplings print loop                                                                                                                                   
-    //cout<< "}," << endl;
-
-
-    prod.push_back(prod_l);
-    dec.push_back(dec_l); 
-    same.push_back(same_l);
-
-  }//end of loop over all the samples
-}
-
-float* MorphWrapper::getWeights(){
-  //morphing class  
-  EFTMorphing * mph  = new EFTMorphing(prod, dec, same);
-  //vector of input couplings for testing point:
-  //same size and same order as basis  
-  //have to change this
-  vector<float> test_p;
-  vector<float> test_d;
-  vector<float> test_s;
-  
-
-  for (unsigned int j  = 0; j<ncouplings; ++j)
-  {
-    if(types[j] == "P")      test_p.push_back(morphed[j]);
-    else if(types[j] == "D") test_d.push_back(morphed[j]);
-    else if(types[j] == "S") test_s.push_back(morphed[j]);
-  }//end of sample couplings print loop                                                                                                                                   
-  //cout << "MORPHING VALUES" << endl;
-  vector<float> mc =  mph->morphingCoefficients(test_p, test_d, test_s);
-
-  ostringstream out_data;
-
-  for(unsigned int i =0;i<mc.size();++i) 
-  { 
-    //cout << fixed << setw( 11 ) << setprecision( 6 ) << mc[i] << endl;
-    weights[i] = mc[i];
-    out_data <<  fixed << setw( 11 ) << setprecision( 6 ) << mc[i] << ' ';
-    //n_eff += mc[i] * cross_sections[i];
-    //cs_norm += TMath::Abs(mc[i])* cross_sections[i];
-  }
-  
-  //  cout<<endl;
-  //  cout<<" Effective number of events: "<<n_eff<<endl;
-  //  std::cout<<"full CS "<<cs_norm<<std::endl;
-
-  //memory cleanup
-  delete mph;
-  mph = 0L;
-  // TODO: This can bee dangereous, have to look for other options
-  //return out_data.str().c_str() ;
-  return weights;
-}
-
-const char* MorphWrapper::getCrossSections(){
-  float kSM     = 0.;
-  float kHZZ    = 0.;
-  float kAZZ    = 0.;
-  float kHWW    = 0.;
-  float kAWW    = 0.;
-  float kHdZ    = 0.;
-  float kHdWR   = 0.;
-  float kHdWI   = 0.;
-  float kHgamgam= 0.;
-  float kAgamgam= 0.;
-  float kHZgam  = 0.;
-  float kAZgam  = 0.;
-  float kHdgam  = 0.;
-  float kHgg	 = 0.;
-  float kAgg    = 0.;
-  float calpha  = 0.707;
-  float dec_f   = 0.1151;
-  ostringstream out_data;
-  // just for energy 8.TeV
-  EFTCrossSection * eft_cs = new EFTCrossSection(8.);
-
-  vector<float> cross_section;
-  float cs;
-  for (int i = 0; i < nsamples; i++){
-    //TODO: For now just working on VBF->4ll data
-    kSM = samples[i][0];
-    kHZZ = samples[i][1]*16.247;
-    kAZZ = samples[i][2]*16.247;
-    cs = eft_cs->vbfToDiFermions(kSM, kHZZ, kAZZ, kHWW, kAWW, kHdZ,  
-                                      kHdWR, kHdWI, kHgamgam, kAgamgam, 
-                                      kHZgam, kAZgam, kHdgam, kHgg, 
-                                      kAgg, calpha,dec_f);
-    //cout << cs << endl;
-    out_data << cs << ' ';
-
-  }
-  delete eft_cs;
-  return out_data.str().c_str();
-}
-
-extern "C"{
-  MorphWrapper* MorphingWrapperNew(){ return new MorphWrapper(); }
-  void setSampleData(MorphWrapper *mw,const char* in_data){return mw->setSampleData(in_data);}
-  float* getWeights(MorphWrapper *mw){ return mw->getWeights();}
-  const char* getCrossSections(MorphWrapper *mw){return mw->getCrossSections();}
-}
-
diff --git a/data/bdt/testdata_0_0.dat b/data/bdt/testdata_0_0.dat
deleted file mode 100644
index 4f5881f..0000000
--- a/data/bdt/testdata_0_0.dat
+++ /dev/null
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diff --git a/data/bdt/testdata_0_1.dat b/data/bdt/testdata_0_1.dat
deleted file mode 100644
index f0f9389..0000000
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diff --git a/data/bdt/testdata_0_2.dat b/data/bdt/testdata_0_2.dat
deleted file mode 100644
index 107f502..0000000
--- a/data/bdt/testdata_0_2.dat
+++ /dev/null
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diff --git a/data/bdt/testdata_1_0.dat b/data/bdt/testdata_1_0.dat
deleted file mode 100644
index 5e18de3..0000000
--- a/data/bdt/testdata_1_0.dat
+++ /dev/null
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diff --git a/data/bdt/testdata_1_1.dat b/data/bdt/testdata_1_1.dat
deleted file mode 100644
index 1fec6eb..0000000
--- a/data/bdt/testdata_1_1.dat
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diff --git a/data/bdt/testdata_1_2.dat b/data/bdt/testdata_1_2.dat
deleted file mode 100644
index 2a5c12e..0000000
--- a/data/bdt/testdata_1_2.dat
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diff --git a/data/bdt/testdata_2_0.dat b/data/bdt/testdata_2_0.dat
deleted file mode 100644
index 597b686..0000000
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diff --git a/data/bdt/testdata_2_1.dat b/data/bdt/testdata_2_1.dat
deleted file mode 100644
index 20b1037..0000000
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diff --git a/data/bdt/testdata_2_2.dat b/data/bdt/testdata_2_2.dat
deleted file mode 100644
index 1e0b01a..0000000
--- a/data/bdt/testdata_2_2.dat
+++ /dev/null
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diff --git a/data/bdt/testdata_F0_F1.dat b/data/bdt/testdata_F0_F1.dat
deleted file mode 100644
index 0a29cb0..0000000
--- a/data/bdt/testdata_F0_F1.dat
+++ /dev/null
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diff --git a/data/bdt/traindata_0_0.dat b/data/bdt/traindata_0_0.dat
deleted file mode 100644
index 41841e3..0000000
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diff --git a/data/bdt/traindata_0_1.dat b/data/bdt/traindata_0_1.dat
deleted file mode 100644
index 71c8fb2..0000000
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diff --git a/data/bdt/traindata_0_2.dat b/data/bdt/traindata_0_2.dat
deleted file mode 100644
index 95bd506..0000000
--- a/data/bdt/traindata_0_2.dat
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diff --git a/data/bdt/traindata_1_0.dat b/data/bdt/traindata_1_0.dat
deleted file mode 100644
index 10b89d9..0000000
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diff --git a/data/bdt/traindata_1_1.dat b/data/bdt/traindata_1_1.dat
deleted file mode 100644
index 5f6ae8d..0000000
--- a/data/bdt/traindata_1_1.dat
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diff --git a/data/bdt/traindata_1_2.dat b/data/bdt/traindata_1_2.dat
deleted file mode 100644
index e746a68..0000000
--- a/data/bdt/traindata_1_2.dat
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diff --git a/data/bdt/traindata_2_0.dat b/data/bdt/traindata_2_0.dat
deleted file mode 100644
index cb88e00..0000000
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diff --git a/data/bdt/traindata_2_1.dat b/data/bdt/traindata_2_1.dat
deleted file mode 100644
index 16ea3de..0000000
--- a/data/bdt/traindata_2_1.dat
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diff --git a/data/bdt/traindata_2_2.dat b/data/bdt/traindata_2_2.dat
deleted file mode 100644
index f240bf7..0000000
--- a/data/bdt/traindata_2_2.dat
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diff --git a/data/bdt/traindata_F0_F1.dat b/data/bdt/traindata_F0_F1.dat
deleted file mode 100644
index 10ad308..0000000
--- a/data/bdt/traindata_F0_F1.dat
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diff --git a/evaluating/plots/xgboost/all_transf_xgboost_hist_v7.png b/evaluating/plots/xgboost/all_transf_xgboost_hist_v7.png
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diff --git a/evaluating/plots/xgboost/roc_eval_10.png b/evaluating/plots/xgboost/roc_eval_10.png
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diff --git a/evaluating/plots/xgboost/roc_eval_20.png b/evaluating/plots/xgboost/roc_eval_20.png
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diff --git a/evaluating/plots/xgboost/roc_eval_5.png b/evaluating/plots/xgboost/roc_eval_5.png
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diff --git a/evaluating/plots/xgboost/roc_eval_50.png b/evaluating/plots/xgboost/roc_eval_50.png
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diff --git a/morph/evmorph_khzz_kazz_11_05_05_3.png b/morph/evmorph_khzz_kazz_11_05_05_3.png
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diff --git a/parametrized-learning/SciKitLearnWrapper/LinkDef.h b/parametrized-learning/SciKitLearnWrapper/LinkDef.h
deleted file mode 100644
index c96a8df..0000000
--- a/parametrized-learning/SciKitLearnWrapper/LinkDef.h
+++ /dev/null
@@ -1,11 +0,0 @@
-#ifdef __CINT__
-
-#pragma link off all globals;
-#pragma link off all classes;
-#pragma link off all functions;
-
-#pragma link C++ class SciKitLearnWrapper;
-#pragma link C++ class SciKitLearnWrapper2d;
-#pragma link C++ class SciKitLearnWrapperNd;
-
-#endif
diff --git a/parametrized-learning/SciKitLearnWrapper/Makefile b/parametrized-learning/SciKitLearnWrapper/Makefile
deleted file mode 100644
index f404202..0000000
--- a/parametrized-learning/SciKitLearnWrapper/Makefile
+++ /dev/null
@@ -1,57 +0,0 @@
-############# MACROS ##############
-
-RC     := root-config
-ifeq ($(shell which $(RC) 2>&1 | sed -ne "s@.*/$(RC)@$(RC)@p"),$(RC))
-MKARCH := $(wildcard $(shell $(RC) --etcdir)/Makefile.arch)
-endif
-ifneq ($(MKARCH),)
-include $(MKARCH)
-else
-ROOTSYS = ../..
-include $(ROOTSYS)/etc/Makefile.arch
-endif
-
-DICT      := SciKitLearnWrapperDict.$(SrcSuf)
-DICTH     := $(DICT:.$(SrcSuf)=.h)
-DICTO     := $(DICT:.$(SrcSuf)=.$(ObjSuf))
-
-SRCS      := $(wildcard *.$(SrcSuf))
-
-HDRS      := $(SRCS:.$(SrcSuf)=.h) LinkDef.h
-HDRS      := $(filter-out $(DICTH),$(HDRS))
-
-TARGETLIB := libSciKitLearnWrapper.$(DllSuf)
-
-OBJS      := $(SRCS:.$(SrcSuf)=.$(ObjSuf))
-
-############# RULES ###############
-
-.$(SrcSuf).$(ObjSuf):
-	$(CXX) `python-config --include` $(CXXFLAGS) -c $<
-
-############# TARGETS #############
-
-.SUFFIXES: .$(SrcSuf) .$(ObjSuf) $(ExeSuf) .$(DllSuf)
-
-all:    $(TARGETLIB)
-
-$(DICT): $(HDRS)
-	@echo "Generating dictionary $@..."
-	$(ROOTCINT)  -f $@ -c  $^
-	#$(ROOTCINT)  -f $@ -c SciKitLearnWrapper.h LinkDef.h
-
-
-$(TARGETLIB): $(OBJS) $(DICTO)
-ifeq ($(PLATFORM),macosx)
-	$(LD) $(SOFLAGS)$@ $(LDFLAGS)  $^ $(OutPutOpt) $@ $(GLIBS) -lRooFit -lRooFitCore -lPython
-else
-	$(LD) $(SOFLAGS) $(LDFLAGS) $^ $(GLIBS) $(OutPutOpt)$@ -lRooFit -lRooFitCore
-endif
-
-distclean: clean
-	@rm -f $(TARGETLIB) $(DICT) $(DICTH)
-
-clean:
-	@rm -f $(OBJS) $(DICTO)
-	@rm SciKitLearnWrapperDict.cxx SciKitLearnWrapperDict.h libSciKitLearnWrapper.so 
-
diff --git a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper.cxx b/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper.cxx
deleted file mode 100644
index fc73220..0000000
--- a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper.cxx
+++ /dev/null
@@ -1,74 +0,0 @@
-/***************************************************************************** 
- * Project: RooFit                                                           * 
- *                                                                           * 
- * This code was autogenerated by RooClassFactory    
- * https://docs.python.org/2/extending/embedding.html#pure-embedding          * 
- *****************************************************************************/ 
-
-// Your description goes here... 
-
-#include "Riostream.h" 
-
-#include "SciKitLearnWrapper.h" 
-#include <math.h> 
-
-#ifndef __CINT__
-#include "Python.h"
-#endif
-
-ClassImp(SciKitLearnWrapper) 
-
-  SciKitLearnWrapper::SciKitLearnWrapper(const char *name, const char *title, 
-                       RooAbsReal& _features) :
-  RooAbsReal(name,title), 
-  features("features","features",this,_features)
- { 
-    m_callback=NULL;
-
- } 
-
-
- SciKitLearnWrapper::SciKitLearnWrapper(const SciKitLearnWrapper& other, const char* name) :  
-  RooAbsReal(other,name), 
-  features("features",this,other.features),
-  m_callback(other.m_callback) { 
- } 
-
-
-
- Double_t SciKitLearnWrapper::evaluate() const 
- { 
-  // ENTER EXPRESSION IN TERMS OF VARIABLE ARGUMENTS HERE 
-  //std::cout << "Hi from C++!" << std::endl;
-  char* blah=NULL;
-  if(    m_callback==NULL) return 0;
-
-  #ifndef __CINT__
-  //PyObject* result = PyObject_CallFunction( m_callback, blah);
-  // cout << "result as long " << PyInt_AsLong(result) << endl;
-  //cout << "result as double " << PyFloat_AsDouble(result) << endl; 
-
-  //cout << "features.arg().getVal() = " << features.arg().getVal() << endl;
-
-  PyObject* arg = PyFloat_FromDouble(features.arg().getVal());
-//  PyObject* result = PyObject_CallObject( m_callback, arg   );
-  PyObject* result = PyObject_CallFunctionObjArgs( m_callback, arg , NULL  );
-  Py_XDECREF( arg );
-
-  double ret;
-  PyArg_Parse((result),"d", &ret);
-  //cout << "from parse " << ret << endl;
-
-  Py_XDECREF( result );
-  #endif
-  return ret ; 
- } 
-
-void SciKitLearnWrapper::RegisterCallBack( PyObject* pyobject )
-{
-	// see http://root.cern.ch/phpBB3/viewtopic.php?t=2606
-	Py_INCREF( pyobject );
-	m_callback = pyobject;
-}
-
-
diff --git a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper.h b/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper.h
deleted file mode 100644
index e1c64c2..0000000
--- a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper.h
+++ /dev/null
@@ -1,50 +0,0 @@
-/*****************************************************************************
- * Project: RooFit                                                           *
- *                                                                           *
-  * This code was autogenerated by RooClassFactory                            * 
- *****************************************************************************/
-
-#ifndef SCIKITLEARNWRAPPER
-#define SCIKITLEARNWRAPPER
-
-#include "RooAbsReal.h"
-#include "RooRealProxy.h"
-#include "RooCategoryProxy.h"
-#include "RooAbsReal.h"
-#include "RooAbsCategory.h"
-
-#ifndef __CINT__
-#include "Python.h"
-#endif
-
-#ifndef PyObject_HEAD
-struct _object;
-typedef _object PyObject;
-#endif
-
-
-class SciKitLearnWrapper : public RooAbsReal{
-public:
-  SciKitLearnWrapper() {} ; 
-  SciKitLearnWrapper(const char *name, const char *title, RooAbsReal& _features);
-  SciKitLearnWrapper(const SciKitLearnWrapper& other, const char* name=0) ;
-  virtual TObject* clone(const char* newname) const { return new SciKitLearnWrapper(*this,newname); }
-  inline virtual ~SciKitLearnWrapper() { }
-
-  void RegisterCallBack( PyObject* pyobject );
-
-  Double_t call_eval(){return evaluate();}
-  Double_t call_getVal(){return getVal();}
-
-protected:
-
-  virtual Double_t evaluate() const ;
-
-private:
-  RooRealProxy features ;  
-
-  PyObject* m_callback;
-  ClassDef(SciKitLearnWrapper,1); // Your description goes here...
-};
- 
-#endif
diff --git a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper2d.cxx b/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper2d.cxx
deleted file mode 100644
index a61abff..0000000
--- a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper2d.cxx
+++ /dev/null
@@ -1,79 +0,0 @@
-/***************************************************************************** 
- * Project: RooFit                                                           * 
- *                                                                           * 
- * This code was autogenerated by RooClassFactory    
- * https://docs.python.org/2/extending/embedding.html#pure-embedding          * 
- *****************************************************************************/ 
-
-// Your description goes here... 
-
-#include "Riostream.h" 
-
-#include "SciKitLearnWrapper2d.h" 
-#include <math.h> 
-
-#ifndef __CINT__
-#include "Python.h"
-#endif
-
-ClassImp(SciKitLearnWrapper2d) 
-
-  SciKitLearnWrapper2d::SciKitLearnWrapper2d(const char *name, const char *title, 
-                       RooAbsReal& _features, RooAbsReal& _params) :
-  RooAbsReal(name,title), 
-  features("features","features",this,_features),
-  params("params","params",this, _params)
- { 
-    m_callback=NULL;
-
- } 
-
-
- SciKitLearnWrapper2d::SciKitLearnWrapper2d(const SciKitLearnWrapper2d& other, const char* name) :  
-  RooAbsReal(other,name), 
-  features("features",this,other.features),
-  params("params","params",this,other.params),
-  m_callback(other.m_callback) { 
- } 
-
-
-
- Double_t SciKitLearnWrapper2d::evaluate() const 
- { 
-  // ENTER EXPRESSION IN TERMS OF VARIABLE ARGUMENTS HERE 
-  //std::cout << "Hi from C++!" << std::endl;
-  #ifndef __CINT__
-  //PyObject* result = PyObject_CallFunction( m_callback, blah);
-  // cout << "result as long " << PyInt_AsLong(result) << endl;
-  //cout << "result as double " << PyFloat_AsDouble(result) << endl; 
-
-  //cout << "features.arg().getVal() = " << features.arg().getVal() << endl;
-  if(    m_callback==NULL) {
-    cout << "no call back set" << endl;
-    return 0;
-  }
-
-  PyObject* arg1 = PyFloat_FromDouble(features.arg().getVal());
-  PyObject* arg2 = PyFloat_FromDouble(params.arg().getVal());
-//  PyObject* result = PyObject_CallObject( m_callback, arg   );
-  PyObject* result = PyObject_CallFunctionObjArgs( m_callback, arg1, arg2 , NULL  );
-  Py_XDECREF( arg1 );
-  Py_XDECREF( arg2 );
-
-  double ret;
-  PyArg_Parse((result),"d", &ret);
-  //cout << "from parse " << ret << endl;
-
-  Py_XDECREF( result );
-  #endif
-  return ret ; 
- } 
-
-void SciKitLearnWrapper2d::RegisterCallBack( PyObject* pyobject )
-{
-	// see http://root.cern.ch/phpBB3/viewtopic.php?t=2606
-	Py_INCREF( pyobject );
-	m_callback = pyobject;
-}
-
-
diff --git a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper2d.h b/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper2d.h
deleted file mode 100644
index 2c64d82..0000000
--- a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapper2d.h
+++ /dev/null
@@ -1,51 +0,0 @@
-/*****************************************************************************
- * Project: RooFit                                                           *
- *                                                                           *
-  * This code was autogenerated by RooClassFactory                            * 
- *****************************************************************************/
-
-#ifndef SCIKITLEARNWRAPPERDD
-#define SCIKITLEARNWRAPPERDD
-
-#include "RooAbsReal.h"
-#include "RooRealProxy.h"
-#include "RooCategoryProxy.h"
-#include "RooAbsReal.h"
-#include "RooAbsCategory.h"
-
-#ifndef __CINT__
-#include "Python.h"
-#endif
-
-#ifndef PyObject_HEAD
-struct _object;
-typedef _object PyObject;
-#endif
-
-
-class SciKitLearnWrapper2d : public RooAbsReal{
-public:
-  SciKitLearnWrapper2d() {} ; 
-  SciKitLearnWrapper2d(const char *name, const char *title, RooAbsReal& _features, RooAbsReal& _params);
-  SciKitLearnWrapper2d(const SciKitLearnWrapper2d& other, const char* name=0) ;
-  virtual TObject* clone(const char* newname) const { return new SciKitLearnWrapper2d(*this,newname); }
-  inline virtual ~SciKitLearnWrapper2d() { }
-
-  void RegisterCallBack( PyObject* pyobject );
-
-  Double_t call_eval(){return evaluate();}
-  Double_t call_getVal(){return getVal();}
-
-protected:
-
-  virtual Double_t evaluate() const ;
-
-private:
-  RooRealProxy features;
-  RooRealProxy params ;  
-
-  PyObject* m_callback;
-  ClassDef(SciKitLearnWrapper2d,1); // Your description goes here...
-};
- 
-#endif
diff --git a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapperNd.cxx b/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapperNd.cxx
deleted file mode 100644
index 3e37ec2..0000000
--- a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapperNd.cxx
+++ /dev/null
@@ -1,112 +0,0 @@
-/***************************************************************************** 
- * Project: RooFit                                                           * 
- *                                                                           * 
- * This code was autogenerated by RooClassFactory    
- * https://docs.python.org/2/extending/embedding.html#pure-embedding          * 
- *****************************************************************************/ 
-
-// Your description goes here... 
-
-#include "Riostream.h" 
-#include "RooErrorHandler.h"
-#include "RooMsgService.h"
-
-#include "SciKitLearnWrapperNd.h" 
-#include <math.h> 
-
-#ifndef __CINT__
-#include "Python.h"
-#endif
-
-ClassImp(SciKitLearnWrapperNd) 
-
-  SciKitLearnWrapperNd::SciKitLearnWrapperNd(const char *name, const char *title, 
-                       RooArgList& _features) :
-  RooAbsReal(name,title), 
-  features("features","features",this)
- { 
-
-   _featureIter = features.createIterator() ;
-  m_callback=NULL;
-
-  TIterator* inputIter1 = _features.createIterator() ;
-  RooAbsArg* comp ;
-  while((comp = (RooAbsArg*)inputIter1->Next())) {
-    if (!dynamic_cast<RooAbsReal*>(comp)) {
-      coutE(InputArguments) << "SciKitLearnWrapperNd::ctor(" << GetName() << ") ERROR: component " << comp->GetName() 
-                            << " in first list is not of type RooAbsReal" << endl ;
-      RooErrorHandler::softAbort() ;
-    }
-    features.add(*comp) ;
-  }
-  delete inputIter1 ;
-
- } 
-
-
- SciKitLearnWrapperNd::SciKitLearnWrapperNd(const SciKitLearnWrapperNd& other, const char* name) :  
-  RooAbsReal(other,name), 
-  features("features",this,other.features),
-  m_callback(other.m_callback) { 
-   _featureIter = features.createIterator() ;
-
- } 
-
- SciKitLearnWrapperNd::SciKitLearnWrapperNd()
- { 
-  // Default constructor
-   _featureIter = NULL;
- } 
-
-
- Double_t SciKitLearnWrapperNd::evaluate() const 
- { 
-  // ENTER EXPRESSION IN TERMS OF VARIABLE ARGUMENTS HERE 
-  //std::cout << "Hi from C++!" << std::endl;
-  #ifndef __CINT__
-  //PyObject* result = PyObject_CallFunction( m_callback, blah);
-  // cout << "result as long " << PyInt_AsLong(result) << endl;
-  //cout << "result as double " << PyFloat_AsDouble(result) << endl; 
-
-  //cout << "features.arg().getVal() = " << features.arg().getVal() << endl;
-  //  features.Print("v");
-  if(    m_callback==NULL) {
-    cout << "no call back set" << endl;
-    return 0;
-  }
-
-
-  double ret =0.;
-  if(features.getSize()==2){
-    TIterator* featureIter = features.createIterator();
-    double first = ((RooAbsReal*)(featureIter->Next()))->getVal();
-    double second = ((RooAbsReal*)(featureIter->Next()))->getVal();
-    //PyObject* arg1 = PyFloat_FromDouble(((RooAbsReal*)(_featureIter->Next()))->getVal());
-    //PyObject* arg2 = PyFloat_FromDouble(((RooAbsReal*)(_featureIter->Next()))->getVal());
-    PyObject* arg1 = PyFloat_FromDouble(first);
-    PyObject* arg2 = PyFloat_FromDouble(second);
-    delete featureIter;
-    //  PyObject* result = PyObject_CallObject( m_callback, arg   );
-    PyObject* result = PyObject_CallFunctionObjArgs( m_callback, arg1, arg2 , NULL  );
-    Py_XDECREF( arg1 );
-    Py_XDECREF( arg2 ); 
-
-    PyArg_Parse((result),"d", &ret);
-    //cout << "from parse " << ret << endl; 
-
-    Py_XDECREF( result );
-    #endif
-  } else {
-    cout <<"only 2d implemented now" << endl;
-  }
-  return ret ; 
- } 
-
-void SciKitLearnWrapperNd::RegisterCallBack( PyObject* pyobject )
-{
-	// see http://root.cern.ch/phpBB3/viewtopic.php?t=2606
-	Py_INCREF( pyobject );
-	m_callback = pyobject;
-}
-
-
diff --git a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapperNd.h b/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapperNd.h
deleted file mode 100644
index 3906c1c..0000000
--- a/parametrized-learning/SciKitLearnWrapper/SciKitLearnWrapperNd.h
+++ /dev/null
@@ -1,53 +0,0 @@
-/*****************************************************************************
- * Project: RooFit                                                           *
- *                                                                           *
-  * This code was autogenerated by RooClassFactory                            * 
- *****************************************************************************/
-
-#ifndef SCIKITLEARNWRAPPERND
-#define SCIKITLEARNWRAPPERND
-
-#include "RooAbsReal.h"
-#include "RooRealProxy.h"
-#include "RooListProxy.h"
-#include "RooCategoryProxy.h"
-#include "RooAbsReal.h"
-#include "RooAbsCategory.h"
-
-#ifndef __CINT__
-#include "Python.h"
-#endif
-
-#ifndef PyObject_HEAD
-struct _object;
-typedef _object PyObject;
-#endif
-
-
-class SciKitLearnWrapperNd : public RooAbsReal{
-public:
-  SciKitLearnWrapperNd(); // need to implement default constructor {} ; 
-  SciKitLearnWrapperNd(const char *name, const char *title, RooArgList& _features);
-  SciKitLearnWrapperNd(const SciKitLearnWrapperNd& other, const char* name=0) ;
-  virtual TObject* clone(const char* newname) const { return new SciKitLearnWrapperNd(*this,newname); }
-  inline virtual ~SciKitLearnWrapperNd() { }
-
-  void RegisterCallBack( PyObject* pyobject );
-
-  Double_t call_eval(){return evaluate();}
-  Double_t call_getVal(){return getVal();}
-
-protected:
-
-  virtual Double_t evaluate() const ;
-
-private:
-  RooListProxy features;
-  mutable TIterator* _featureIter ;  //! Iterator over paramSet
-
-
-  PyObject* m_callback;
-  ClassDef(SciKitLearnWrapperNd,1); // Your description goes here...
-};
- 
-#endif
diff --git a/parametrized-learning/SciKitLearnWrapper/scikitlearn-wrapper-plot.pdf b/parametrized-learning/SciKitLearnWrapper/scikitlearn-wrapper-plot.pdf
deleted file mode 100644
index 0dd0a6a..0000000
Binary files a/parametrized-learning/SciKitLearnWrapper/scikitlearn-wrapper-plot.pdf and /dev/null differ
diff --git a/parametrized-learning/SciKitLearnWrapper/test.C b/parametrized-learning/SciKitLearnWrapper/test.C
deleted file mode 100644
index 2a5c920..0000000
--- a/parametrized-learning/SciKitLearnWrapper/test.C
+++ /dev/null
@@ -1,19 +0,0 @@
-test(){
-	gSystem->Load("libSciKitLearnWrapper.so");
-	RooWorkspace w("w");
-	w.factory("x[-5,5]");
-	w.factory("mu[-5,5]");
-	w.defineSet("myset","x,mu")
-	w.factory("SciKitLearnWrapper::nn(x)");
-	RooArgList list;
-	list.add(*w.var("x"));
-	list.add(*w.var("mu"));
-	test = SciKitLearnWrapperNd("test","test",list);
-	w.import(test);
-	test2 = SciKitLearnWrapper2d("test2","test",*w.var("x"),*w.var("mu"));
-	w.import(test2);
-	w.Print();
-
-	//	w.factory("SciKitLearnWrapper2d::nndd(x,mu)");
-
-}
diff --git a/parametrized-learning/SciKitLearnWrapper/testWrapper.py b/parametrized-learning/SciKitLearnWrapper/testWrapper.py
deleted file mode 100644
index a54ccb4..0000000
--- a/parametrized-learning/SciKitLearnWrapper/testWrapper.py
+++ /dev/null
@@ -1,59 +0,0 @@
-from ROOT import *
-
-import numpy as np
-from sklearn import svm
-from sklearn.externals import joblib
-
-def simpleTest():
-	print "Simple Test"
-	gSystem.Load( 'libSciKitLearnWrapper' )	
-
-	def SayHi():
-	   print 'Hi from python!'
-	   return 3.	
-
-	x = RooRealVar('x','x',0,1)
-	s = SciKitLearnWrapper('s','s',x)
-	s.RegisterCallBack( SayHi );
-	print "\ngetVal"
-	s.getVal()
-
-
-def inOutFunc(x=0.):
-	print "inouttest input was", x
-	return x
-
-def inOutTest():
-	gSystem.Load( 'libSciKitLearnWrapper' )	
-	x = RooRealVar('x','x',0,1)
-	s = SciKitLearnWrapper('s','s',x)
-	s.RegisterCallBack( inOutFunc );
-	print "\ngetVal"
-	print s.getVal()
-
-
-def scikitlearnFunc(x=0.):
-	#print "scikitlearnTest"
-	clf = joblib.load('../adaptive.pkl') 
-	#print "inouttest input was", x
-	traindata = np.array((x,0.))
-	outputs=clf.predict(traindata)
-	#print x, outputs
-	return outputs[0]
-
-def scikitlearnTest():
-	gSystem.Load( 'libSciKitLearnWrapper' )	
-	x = RooRealVar('x','x',0.2,-5,5)	
-	s = SciKitLearnWrapper('s','s',x)
-	s.RegisterCallBack( scikitlearnFunc );
-
-	c1 = TCanvas('c1')
-	frame = x.frame()
-	s.plotOn(frame)
-	frame.Draw()
-	c1.SaveAs('scikitlearn-wrapper-plot.pdf')
-
-if __name__ == '__main__':
-	#simpleTest()
-	#inOutTest()
-	scikitlearnTest()
\ No newline at end of file
diff --git a/plots/bdt/composite_trained_bdt_diff.png b/plots/bdt/composite_trained_bdt_diff.png
deleted file mode 100644
index 943c538..0000000
Binary files a/plots/bdt/composite_trained_bdt_diff.png and /dev/null differ
diff --git a/plots/bdt/composite_trained_bdt_diff.txt b/plots/bdt/composite_trained_bdt_diff.txt
deleted file mode 100644
index bb54937..0000000
--- a/plots/bdt/composite_trained_bdt_diff.txt
+++ /dev/null
@@ -1,100 +0,0 @@
--7.269088913120702600e-02
--3.648321628447348530e-02
--8.384684050145363443e-03
-1.319162801093853865e-02
-2.964625161268408249e-02
-4.214450507543276991e-02
-5.161968930796789756e-02
-5.880066269045358673e-02
-9.639127813425574232e-03
-1.377656368377033758e-02
-7.146404035285991441e-03
-9.548832655051908702e-03
-1.138547102602927019e-02
-1.279214724392763181e-02
-9.460821255149243214e-03
-1.028812427953185171e-02
-1.092175718292986986e-02
-9.065334697757387872e-03
-9.431553387140523270e-03
-9.705382888804736652e-03
-1.058967943547695079e-02
-9.320120738046222542e-03
-9.412468430376019768e-03
-8.740082514602676156e-03
-8.757262469786475378e-03
-8.744139784875981647e-03
-8.501256665977452442e-03
-8.435478812460539544e-03
-8.231850115214767172e-03
-8.117808171654861127e-03
-7.878134120148372332e-03
--6.352780848007277825e-03
--6.601021012683450095e-03
--6.847133586964426755e-03
--7.105190194710786500e-03
--7.391311721627102926e-03
--7.716498031898000320e-03
--8.125065204827031096e-03
--8.569272883547807140e-03
--9.044016603196203263e-03
-8.061046533172522288e-03
-7.432891657044526923e-03
-3.120047657391689100e-02
-2.049171697811602577e-02
-1.958238317871741074e-02
-1.855551139673661254e-02
-1.738376753467063551e-02
-7.079878319862897840e-03
-2.802607388436340052e-02
-2.627211503586801555e-02
-6.529930904882874643e-02
-3.818876625348677223e-02
-3.553614545877414876e-02
-5.689202728029063572e-02
-9.649474199033614141e-02
-8.288059330088914933e-02
-8.792539184688985543e-02
--6.732216431515292143e-02
-9.094382730265260228e-02
-8.412964675027279071e-02
-1.493477143259931417e-01
--1.212556107906404002e-02
-2.486567970521775806e-01
-1.761842848714862964e-01
-2.321653554785898521e-01
-2.287234971452660748e-01
-8.564344207949603494e-02
-1.913786285183043390e-01
-2.218728750021337071e-01
-1.036905581303034785e-01
-2.630815717824818156e-01
-3.355254223964734273e-01
-1.035934546190671046e-01
-4.127316459628915801e-02
-4.702355511878331118e-02
-1.676651596117602061e-01
-5.188311937105716254e-02
-1.005017269794787893e-01
-9.337145475926345028e-03
-8.129112992643938718e-02
-7.063958458745200897e-02
-1.689824870370371102e-02
-2.939084913337486338e-02
-2.253607094476328676e-02
-1.673388234636707939e-02
-2.256916287279686628e-02
-1.850970034416432597e-02
-1.267093211390146745e-02
-9.906936408034305863e-03
-7.645461770274808444e-03
-1.299850289036463824e-02
-1.150658545191751703e-02
-2.101551234764520437e-03
-1.133981638962500149e-03
-3.592196916447631949e-04
--2.589902955303369225e-04
--7.506235992691401293e-04
--1.140340748974066898e-03
--1.448320124216806448e-03
--1.691592724896939792e-03
diff --git a/plots/bdt/composite_trained_bdt_ratio.png b/plots/bdt/composite_trained_bdt_ratio.png
deleted file mode 100644
index 02c9dbe..0000000
Binary files a/plots/bdt/composite_trained_bdt_ratio.png and /dev/null differ
diff --git a/plots/bdt/composite_trained_bdt_ratio.txt b/plots/bdt/composite_trained_bdt_ratio.txt
deleted file mode 100644
index 6ca5a1b..0000000
--- a/plots/bdt/composite_trained_bdt_ratio.txt
+++ /dev/null
@@ -1,100 +0,0 @@
-1.083401270014240358e+00
-1.083401270014240358e+00
-1.083401270014240358e+00
-1.083401270014240358e+00
-1.083401270014240358e+00
-1.083401270014240358e+00
-1.083401270014240358e+00
-1.083401270014240358e+00
-1.138009355368045927e+00
-1.138009355368045927e+00
-1.147788801815784243e+00
-1.147788801815784243e+00
-1.147788801815784243e+00
-1.147788801815784243e+00
-1.152198799998592538e+00
-1.152198799998592538e+00
-1.152198799998592538e+00
-1.154538706734450582e+00
-1.154538706734450582e+00
-1.154538706734450582e+00
-1.153854677897309555e+00
-1.155265178633731571e+00
-1.155265178633731571e+00
-1.155989354829282556e+00
-1.155989354829282556e+00
-1.155989354829282556e+00
-1.156191815403687873e+00
-1.156191815403687873e+00
-1.156305376804763307e+00
-1.156305376804763307e+00
-1.156406684767366189e+00
-1.170473949676898773e+00
-1.170531712515540335e+00
-1.170558397377891691e+00
-1.170565355921475037e+00
-1.170565355921475037e+00
-1.170565355921475037e+00
-1.170604868364096163e+00
-1.170630492850644355e+00
-1.170630492850644355e+00
-1.152986782131754540e+00
-1.153003365482585973e+00
-1.128540793521628505e+00
-1.138458960040972467e+00
-1.138467941499964109e+00
-1.138468281926631187e+00
-1.138468281926631187e+00
-1.147433174260083621e+00
-1.124955240752902430e+00
-1.124955298603211196e+00
-1.083918157488211298e+00
-1.108723806315147664e+00
-1.108732101216550747e+00
-1.084341847266628633e+00
-1.041257494977649856e+00
-1.050878578915687589e+00
-1.041258079825375882e+00
-1.191269299451072072e+00
-1.027022319508998471e+00
-1.027022319508998471e+00
-9.540662389212299921e-01
-1.106788510275027670e+00
-8.361594067429509725e-01
-8.976194578298042348e-01
-8.294107451499672656e-01
-8.193895846354677381e-01
-9.477894233829080584e-01
-8.262217643589824245e-01
-7.788607649947318912e-01
-8.793156700108228918e-01
-7.015634122091523039e-01
-6.103961991333565207e-01
-8.235451994309928025e-01
-8.673376128614060931e-01
-8.436204380571012962e-01
-7.058501720461795026e-01
-8.055728611751058477e-01
-7.421381892669697278e-01
-8.198418617862329727e-01
-7.358332187120140144e-01
-7.358330393393230917e-01
-7.802775143109519362e-01
-7.597612406965852383e-01
-7.597613520252168851e-01
-7.597611582039661693e-01
-7.490547344507556549e-01
-7.490551864542309701e-01
-7.515342968480315244e-01
-7.515342968480315244e-01
-7.515342968480315244e-01
-7.443401946972854066e-01
-7.443401921610196537e-01
-7.525413699700111980e-01
-7.525413699700111980e-01
-7.525413605948907403e-01
-7.525413605948907403e-01
-7.525413601872776859e-01
-7.525413601872776859e-01
-7.525413699700111980e-01
-7.525420062402725652e-01
diff --git a/plots/bdt/composite_trained_bdt_roc.png b/plots/bdt/composite_trained_bdt_roc.png
deleted file mode 100644
index 5008764..0000000
Binary files a/plots/bdt/composite_trained_bdt_roc.png and /dev/null differ
diff --git a/plots/bdt/composite_trained_bdt_roc.txt b/plots/bdt/composite_trained_bdt_roc.txt
deleted file mode 100644
index f236d6b..0000000
--- a/plots/bdt/composite_trained_bdt_roc.txt
+++ /dev/null
@@ -1,188 +0,0 @@
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diff --git a/plots/bdt/decomposed_trained_f1_f0_bdt_multi_scatter_regression.txt b/plots/bdt/decomposed_trained_f1_f0_bdt_multi_scatter_regression.txt
deleted file mode 100644
index bd239f4..0000000
--- a/plots/bdt/decomposed_trained_f1_f0_bdt_multi_scatter_regression.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f1_f0_bdt_multi_scatter_score.txt b/plots/bdt/decomposed_trained_f1_f0_bdt_multi_scatter_score.txt
deleted file mode 100644
index 545696f..0000000
--- a/plots/bdt/decomposed_trained_f1_f0_bdt_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f1_f0_bdt_multi_scatter_target.txt b/plots/bdt/decomposed_trained_f1_f0_bdt_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/bdt/decomposed_trained_f1_f0_bdt_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f1_f0_bdt_ratio.png b/plots/bdt/decomposed_trained_f1_f0_bdt_ratio.png
deleted file mode 100644
index 673a65c..0000000
Binary files a/plots/bdt/decomposed_trained_f1_f0_bdt_ratio.png and /dev/null differ
diff --git a/plots/bdt/decomposed_trained_f1_f0_bdt_ratio_trained.txt b/plots/bdt/decomposed_trained_f1_f0_bdt_ratio_trained.txt
deleted file mode 100644
index 17cc967..0000000
--- a/plots/bdt/decomposed_trained_f1_f0_bdt_ratio_trained.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f1_f1_bdt_multi_scatter_regression.txt b/plots/bdt/decomposed_trained_f1_f1_bdt_multi_scatter_regression.txt
deleted file mode 100644
index c09ae18..0000000
--- a/plots/bdt/decomposed_trained_f1_f1_bdt_multi_scatter_regression.txt
+++ /dev/null
@@ -1,6000 +0,0 @@
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diff --git a/plots/bdt/decomposed_trained_f1_f1_bdt_multi_scatter_score.txt b/plots/bdt/decomposed_trained_f1_f1_bdt_multi_scatter_score.txt
deleted file mode 100644
index da562ea..0000000
--- a/plots/bdt/decomposed_trained_f1_f1_bdt_multi_scatter_score.txt
+++ /dev/null
@@ -1,6000 +0,0 @@
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diff --git a/plots/bdt/decomposed_trained_f1_f1_bdt_multi_scatter_target.txt b/plots/bdt/decomposed_trained_f1_f1_bdt_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/bdt/decomposed_trained_f1_f1_bdt_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f1_f2_bdt_dist.png b/plots/bdt/decomposed_trained_f1_f2_bdt_dist.png
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diff --git a/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter.png b/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter.png
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diff --git a/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_LRs.txt b/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_LRs.txt
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--- a/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_LRs.txt
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diff --git a/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_regression.txt b/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_regression.txt
deleted file mode 100644
index 91143f5..0000000
--- a/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_regression.txt
+++ /dev/null
@@ -1,6000 +0,0 @@
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diff --git a/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_score.txt b/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_score.txt
deleted file mode 100644
index fde15e1..0000000
--- a/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_target.txt b/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/bdt/decomposed_trained_f1_f2_bdt_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f1_f2_bdt_ratio.png b/plots/bdt/decomposed_trained_f1_f2_bdt_ratio.png
deleted file mode 100644
index 6cd5d77..0000000
Binary files a/plots/bdt/decomposed_trained_f1_f2_bdt_ratio.png and /dev/null differ
diff --git a/plots/bdt/decomposed_trained_f1_f2_bdt_ratio_trained.txt b/plots/bdt/decomposed_trained_f1_f2_bdt_ratio_trained.txt
deleted file mode 100644
index 99beac0..0000000
--- a/plots/bdt/decomposed_trained_f1_f2_bdt_ratio_trained.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f1_f2_bdt_ratio_truth.txt b/plots/bdt/decomposed_trained_f1_f2_bdt_ratio_truth.txt
deleted file mode 100644
index 5c69bcd..0000000
--- a/plots/bdt/decomposed_trained_f1_f2_bdt_ratio_truth.txt
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diff --git a/plots/bdt/decomposed_trained_f2_f0_bdt_multi_scatter_regression.txt b/plots/bdt/decomposed_trained_f2_f0_bdt_multi_scatter_regression.txt
deleted file mode 100644
index b924e60..0000000
--- a/plots/bdt/decomposed_trained_f2_f0_bdt_multi_scatter_regression.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f2_f0_bdt_multi_scatter_score.txt b/plots/bdt/decomposed_trained_f2_f0_bdt_multi_scatter_score.txt
deleted file mode 100644
index 664812c..0000000
--- a/plots/bdt/decomposed_trained_f2_f0_bdt_multi_scatter_score.txt
+++ /dev/null
@@ -1,6000 +0,0 @@
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diff --git a/plots/bdt/decomposed_trained_f2_f0_bdt_multi_scatter_target.txt b/plots/bdt/decomposed_trained_f2_f0_bdt_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/bdt/decomposed_trained_f2_f0_bdt_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f2_f0_bdt_ratio.png b/plots/bdt/decomposed_trained_f2_f0_bdt_ratio.png
deleted file mode 100644
index 69f687d..0000000
Binary files a/plots/bdt/decomposed_trained_f2_f0_bdt_ratio.png and /dev/null differ
diff --git a/plots/bdt/decomposed_trained_f2_f0_bdt_ratio_trained.txt b/plots/bdt/decomposed_trained_f2_f0_bdt_ratio_trained.txt
deleted file mode 100644
index 081c7e9..0000000
--- a/plots/bdt/decomposed_trained_f2_f0_bdt_ratio_trained.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f2_f1_bdt_multi_scatter_regression.txt b/plots/bdt/decomposed_trained_f2_f1_bdt_multi_scatter_regression.txt
deleted file mode 100644
index 703a03e..0000000
--- a/plots/bdt/decomposed_trained_f2_f1_bdt_multi_scatter_regression.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f2_f1_bdt_multi_scatter_score.txt b/plots/bdt/decomposed_trained_f2_f1_bdt_multi_scatter_score.txt
deleted file mode 100644
index 497fb5e..0000000
--- a/plots/bdt/decomposed_trained_f2_f1_bdt_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f2_f1_bdt_multi_scatter_target.txt b/plots/bdt/decomposed_trained_f2_f1_bdt_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/bdt/decomposed_trained_f2_f1_bdt_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/bdt/decomposed_trained_f2_f1_bdt_ratio_trained.txt b/plots/bdt/decomposed_trained_f2_f1_bdt_ratio_trained.txt
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diff --git a/plots/bdt/decomposed_trained_f2_f2_bdt_multi_scatter_regression.txt b/plots/bdt/decomposed_trained_f2_f2_bdt_multi_scatter_regression.txt
deleted file mode 100644
index c09ae18..0000000
--- a/plots/bdt/decomposed_trained_f2_f2_bdt_multi_scatter_regression.txt
+++ /dev/null
@@ -1,6000 +0,0 @@
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diff --git a/plots/bdt/decomposed_trained_f2_f2_bdt_multi_scatter_score.txt b/plots/bdt/decomposed_trained_f2_f2_bdt_multi_scatter_score.txt
deleted file mode 100644
index 56ce43b..0000000
--- a/plots/bdt/decomposed_trained_f2_f2_bdt_multi_scatter_score.txt
+++ /dev/null
@@ -1,6000 +0,0 @@
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diff --git a/plots/bdt/decomposed_trained_f2_f2_bdt_multi_scatter_target.txt b/plots/bdt/decomposed_trained_f2_f2_bdt_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/bdt/decomposed_trained_f2_f2_bdt_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/bdt/full_trained_bdt_multi_scatter_score.txt b/plots/bdt/full_trained_bdt_multi_scatter_score.txt
deleted file mode 100644
index 8993a6e..0000000
--- a/plots/bdt/full_trained_bdt_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/bdt/full_trained_bdt_ratio.png b/plots/bdt/full_trained_bdt_ratio.png
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diff --git a/plots/bdt/full_trained_bdt_ratio.txt b/plots/bdt/full_trained_bdt_ratio.txt
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diff --git a/plots/bdt/full_truth_bdt_ratio.png b/plots/bdt/full_truth_bdt_ratio.png
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diff --git a/plots/bdt/full_truth_bdt_ratio.txt b/plots/bdt/full_truth_bdt_ratio.txt
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index bcf7df5..0000000
--- a/plots/bdt/full_truth_bdt_ratio.txt
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diff --git a/plots/logistic/decomposed_trained_f1_f0_logistic_multi_scatter_regression.txt b/plots/logistic/decomposed_trained_f1_f0_logistic_multi_scatter_regression.txt
deleted file mode 100644
index 8e6ffbc..0000000
--- a/plots/logistic/decomposed_trained_f1_f0_logistic_multi_scatter_regression.txt
+++ /dev/null
@@ -1,6000 +0,0 @@
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diff --git a/plots/logistic/decomposed_trained_f1_f0_logistic_multi_scatter_score.txt b/plots/logistic/decomposed_trained_f1_f0_logistic_multi_scatter_score.txt
deleted file mode 100644
index b74789c..0000000
--- a/plots/logistic/decomposed_trained_f1_f0_logistic_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f1_f0_logistic_multi_scatter_target.txt b/plots/logistic/decomposed_trained_f1_f0_logistic_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/logistic/decomposed_trained_f1_f0_logistic_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f1_f0_logistic_ratio.txt b/plots/logistic/decomposed_trained_f1_f0_logistic_ratio.txt
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index 970e4fd..0000000
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diff --git a/plots/logistic/decomposed_trained_f1_f0_logistic_ratio_truth.txt b/plots/logistic/decomposed_trained_f1_f0_logistic_ratio_truth.txt
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index 5c69bcd..0000000
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diff --git a/plots/logistic/decomposed_trained_f1_f0_logistic_scatter.txt b/plots/logistic/decomposed_trained_f1_f0_logistic_scatter.txt
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diff --git a/plots/logistic/decomposed_trained_f1_f1_logistic_multi_scatter_score.txt b/plots/logistic/decomposed_trained_f1_f1_logistic_multi_scatter_score.txt
deleted file mode 100644
index a5f787e..0000000
--- a/plots/logistic/decomposed_trained_f1_f1_logistic_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f1_f1_logistic_multi_scatter_target.txt b/plots/logistic/decomposed_trained_f1_f1_logistic_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/logistic/decomposed_trained_f1_f1_logistic_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f1_f2_logistic_multi_scatter_regression.txt b/plots/logistic/decomposed_trained_f1_f2_logistic_multi_scatter_regression.txt
deleted file mode 100644
index 572e7ef..0000000
--- a/plots/logistic/decomposed_trained_f1_f2_logistic_multi_scatter_regression.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f1_f2_logistic_multi_scatter_score.txt b/plots/logistic/decomposed_trained_f1_f2_logistic_multi_scatter_score.txt
deleted file mode 100644
index 404dfe4..0000000
--- a/plots/logistic/decomposed_trained_f1_f2_logistic_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f1_f2_logistic_multi_scatter_target.txt b/plots/logistic/decomposed_trained_f1_f2_logistic_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/logistic/decomposed_trained_f1_f2_logistic_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f2_f0_logistic_multi_scatter_regression.txt b/plots/logistic/decomposed_trained_f2_f0_logistic_multi_scatter_regression.txt
deleted file mode 100644
index aad233a..0000000
--- a/plots/logistic/decomposed_trained_f2_f0_logistic_multi_scatter_regression.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f2_f0_logistic_multi_scatter_score.txt b/plots/logistic/decomposed_trained_f2_f0_logistic_multi_scatter_score.txt
deleted file mode 100644
index dbd6d8b..0000000
--- a/plots/logistic/decomposed_trained_f2_f0_logistic_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f2_f0_logistic_multi_scatter_target.txt b/plots/logistic/decomposed_trained_f2_f0_logistic_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/logistic/decomposed_trained_f2_f0_logistic_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f2_f0_logistic_ratio.png b/plots/logistic/decomposed_trained_f2_f0_logistic_ratio.png
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index cde6088..0000000
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diff --git a/plots/logistic/decomposed_trained_f2_f0_logistic_ratio.txt b/plots/logistic/decomposed_trained_f2_f0_logistic_ratio.txt
deleted file mode 100644
index 63f4f3d..0000000
--- a/plots/logistic/decomposed_trained_f2_f0_logistic_ratio.txt
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diff --git a/plots/logistic/decomposed_trained_f2_f0_logistic_ratio_trained.txt b/plots/logistic/decomposed_trained_f2_f0_logistic_ratio_trained.txt
deleted file mode 100644
index 03befe2..0000000
--- a/plots/logistic/decomposed_trained_f2_f0_logistic_ratio_trained.txt
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diff --git a/plots/logistic/decomposed_trained_f2_f1_logistic_multi_scatter_regression.txt b/plots/logistic/decomposed_trained_f2_f1_logistic_multi_scatter_regression.txt
deleted file mode 100644
index a5ec463..0000000
--- a/plots/logistic/decomposed_trained_f2_f1_logistic_multi_scatter_regression.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f2_f1_logistic_multi_scatter_score.txt b/plots/logistic/decomposed_trained_f2_f1_logistic_multi_scatter_score.txt
deleted file mode 100644
index b349ac0..0000000
--- a/plots/logistic/decomposed_trained_f2_f1_logistic_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f2_f1_logistic_multi_scatter_target.txt b/plots/logistic/decomposed_trained_f2_f1_logistic_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/logistic/decomposed_trained_f2_f1_logistic_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f2_f1_logistic_ratio.txt b/plots/logistic/decomposed_trained_f2_f1_logistic_ratio.txt
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diff --git a/plots/logistic/decomposed_trained_f2_f1_logistic_ratio_trained.txt b/plots/logistic/decomposed_trained_f2_f1_logistic_ratio_trained.txt
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diff --git a/plots/logistic/decomposed_trained_f2_f1_logistic_ratio_truth.txt b/plots/logistic/decomposed_trained_f2_f1_logistic_ratio_truth.txt
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index d015561..0000000
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diff --git a/plots/logistic/decomposed_trained_f2_f2_logistic_multi_scatter_score.txt b/plots/logistic/decomposed_trained_f2_f2_logistic_multi_scatter_score.txt
deleted file mode 100644
index 7cebd7a..0000000
--- a/plots/logistic/decomposed_trained_f2_f2_logistic_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_trained_f2_f2_logistic_multi_scatter_target.txt b/plots/logistic/decomposed_trained_f2_f2_logistic_multi_scatter_target.txt
deleted file mode 100644
index 900d113..0000000
--- a/plots/logistic/decomposed_trained_f2_f2_logistic_multi_scatter_target.txt
+++ /dev/null
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diff --git a/plots/logistic/decomposed_truth_f1_f0_logistic_roc.png b/plots/logistic/decomposed_truth_f1_f0_logistic_roc.png
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diff --git a/plots/logistic/decomposed_truth_f1_f0_logistic_roc.txt b/plots/logistic/decomposed_truth_f1_f0_logistic_roc.txt
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diff --git a/plots/logistic/full_trained_logistic_multi_scatter_regression.txt b/plots/logistic/full_trained_logistic_multi_scatter_regression.txt
deleted file mode 100644
index 4b93b70..0000000
--- a/plots/logistic/full_trained_logistic_multi_scatter_regression.txt
+++ /dev/null
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diff --git a/plots/logistic/full_trained_logistic_multi_scatter_score.txt b/plots/logistic/full_trained_logistic_multi_scatter_score.txt
deleted file mode 100644
index 812cde6..0000000
--- a/plots/logistic/full_trained_logistic_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/logistic/full_trained_logistic_ratio.png b/plots/logistic/full_trained_logistic_ratio.png
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diff --git a/plots/logistic/full_trained_logistic_ratio.txt b/plots/logistic/full_trained_logistic_ratio.txt
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diff --git a/plots/svc/decomposed_trained_f1_f0_svc_multi_scatter_score.txt b/plots/svc/decomposed_trained_f1_f0_svc_multi_scatter_score.txt
deleted file mode 100644
index a4c65ef..0000000
--- a/plots/svc/decomposed_trained_f1_f0_svc_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/svc/decomposed_trained_f1_f1_svc_multi_scatter_score.txt b/plots/svc/decomposed_trained_f1_f1_svc_multi_scatter_score.txt
deleted file mode 100644
index c09ae18..0000000
--- a/plots/svc/decomposed_trained_f1_f1_svc_multi_scatter_score.txt
+++ /dev/null
@@ -1,6000 +0,0 @@
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diff --git a/plots/svc/decomposed_trained_f1_f2_svc_multi_scatter_score.txt b/plots/svc/decomposed_trained_f1_f2_svc_multi_scatter_score.txt
deleted file mode 100644
index 75108bb..0000000
--- a/plots/svc/decomposed_trained_f1_f2_svc_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/svc/decomposed_trained_f1_f2_svc_scatter.txt b/plots/svc/decomposed_trained_f1_f2_svc_scatter.txt
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diff --git a/plots/svc/decomposed_trained_f2_f0_svc_multi_scatter_score.txt b/plots/svc/decomposed_trained_f2_f0_svc_multi_scatter_score.txt
deleted file mode 100644
index 6de64aa..0000000
--- a/plots/svc/decomposed_trained_f2_f0_svc_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/svc/decomposed_trained_f2_f0_svc_ratio.png b/plots/svc/decomposed_trained_f2_f0_svc_ratio.png
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diff --git a/plots/svc/decomposed_trained_f2_f1_svc_multi_scatter_score.txt b/plots/svc/decomposed_trained_f2_f1_svc_multi_scatter_score.txt
deleted file mode 100644
index 02d5333..0000000
--- a/plots/svc/decomposed_trained_f2_f1_svc_multi_scatter_score.txt
+++ /dev/null
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diff --git a/plots/svc/decomposed_trained_f2_f2_svc_multi_scatter_score.txt b/plots/svc/decomposed_trained_f2_f2_svc_multi_scatter_score.txt
deleted file mode 100644
index c09ae18..0000000
--- a/plots/svc/decomposed_trained_f2_f2_svc_multi_scatter_score.txt
+++ /dev/null
@@ -1,6000 +0,0 @@
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diff --git a/plots/svc/decomposed_truth_f1_f0_svc_roc.txt b/plots/svc/decomposed_truth_f1_f0_svc_roc.txt
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diff --git a/plots/svc/full_trained_svc_multi_scatter_score.txt b/plots/svc/full_trained_svc_multi_scatter_score.txt
deleted file mode 100644
index 921e581..0000000
--- a/plots/svc/full_trained_svc_multi_scatter_score.txt
+++ /dev/null
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index 7d3da55..0000000
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diff --git a/plots/svr/decomposed_trained_f1_f2_svr_ratio_truth.txt b/plots/svr/decomposed_trained_f1_f2_svr_ratio_truth.txt
deleted file mode 100644
index ff96c93..0000000
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diff --git a/plots/svr/decomposed_trained_f1_f2_svr_scatter.txt b/plots/svr/decomposed_trained_f1_f2_svr_scatter.txt
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diff --git a/plots/svr/decomposed_trained_f2_f0_svr_scatter.txt b/plots/svr/decomposed_trained_f2_f0_svr_scatter.txt
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diff --git a/plots/svr/decomposed_trained_f2_f1_svr_scatter.png b/plots/svr/decomposed_trained_f2_f1_svr_scatter.png
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diff --git a/plots/svr/decomposed_trained_f2_f1_svr_scatter.txt b/plots/svr/decomposed_trained_f2_f1_svr_scatter.txt
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diff --git a/plots/svr/full_truth_svr_ratio.png b/plots/svr/full_truth_svr_ratio.png
deleted file mode 100644
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diff --git a/plots/svr/full_truth_svr_ratio.txt b/plots/svr/full_truth_svr_ratio.txt
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diff --git a/scripts/ploting_sesion.py b/scripts/ploting_sesion.py
deleted file mode 100644
index 094b594..0000000
--- a/scripts/ploting_sesion.py
+++ /dev/null
@@ -1,147 +0,0 @@
-# coding: utf-8
-import numpy as np
-import matplotlib.pyplot as plt
-# Printing final comp ratios for different classsifiers
-c_ratio_log = np.loadtxt('../plots/mlp/results/comp_train_mlp_ratio.txt')
-c_ratio_svr = np.loadtxt('../plots/logistic/results/comp_train_logistic_ratio.txt')
-c_ratio_svc = np.loadtxt('../plots/bdt/results/comp_train_bdt_ratio.txt')
-c_ratio = np.loadtxt('../plots/mlp/results/full_truth_mlp_ratio.txt')
-x = np.linspace(0,5,100)
-log = plt.plot(x, c_ratio_log, label='MLP')
-svr = plt.plot(x, c_ratio_svr, label='Logistic')
-svc = plt.plot(x, c_ratio_svc, label='BDT')
-ratio = plt.plot(x, c_ratio, label='Ratio')
-plt.xlabel('x')
-plt.ylabel('LR')
-plt.legend()
-plt.savefig('../plots/comp_train_all_ratio.png')
-c_diff_log = np.loadtxt('../plots/mlp/results/comp_train_mlp_diff.txt')
-c_diff_svr = np.loadtxt('../plots/logistic/results/comp_train_logistic_diff.txt')
-c_diff_svc = np.loadtxt('../plots/bdt/results/comp_train_bdt_diff.txt')
-plt.clf()
-log_dif = plt.plot(x, c_diff_log, label='MLP')
-svr_dif = plt.plot(x, c_diff_svr, label='Logistic')
-svc_dif = plt.plot(x, c_diff_svc, label='BDT')
-plt.xlabel('x')
-plt.ylabel('differences')
-plt.legend()
-plt.savefig('../plots/comp_train_all_diff.png')
-plt.clf()
-# Ratios for mlp
-# full-truth to full-train to composed-train comparison
-c_full_log = np.loadtxt('../plots/mlp/results/full_train_mlp_ratio.txt')
-log = plt.plot(x, c_ratio_log, label='Composite train')
-full = plt.plot(x, c_full_log, label='Full train')
-ratio = plt.plot(x, c_ratio, label='Full truth')
-plt.xlabel('x')
-plt.ylabel('LR')
-plt.title('Likelihood ratios for MLP')
-plt.legend()
-plt.savefig('../plots/full_comparison_mlp_ratio.png')
-plt.clf()
-c_full_diff = np.loadtxt('../plots/mlp/results/full_train_mlp_diff.txt')
-plt.plot(x, c_full_diff, label="Full")
-plt.plot(x, c_diff_log, label="Composite")
-plt.xlabel('x')
-plt.ylabel('difference')
-plt.legend()
-plt.title('Differences to truth ratio for MLP')
-plt.savefig('../plots/full_comparison_mlp_diff.png')
-plt.clf()
-# ROC curves comparison
-roc_comp = np.loadtxt('../plots/mlp/results/comp_train_mlp_sigbkg.txt')
-roc_full = np.loadtxt('../plots/mlp/results/full_train_mlp_sigbkg.txt')
-roc_truth = np.loadtxt('../plots/mlp/results/full_truth_mlp_sigbkg.txt')
-from sklearn.metrics import roc_curve, auc
-roc_comp_auc = auc(roc_comp[:,1],1.-roc_comp[:,0])
-roc_full_auc = auc(roc_full[:,1],1.-roc_full[:,0])
-roc_truth_auc = auc(roc_truth[:,1],1.-roc_truth[:,0])
-plt.figure()
-plt.plot(roc_comp[:,1], 1.-roc_comp[:,0], label='Sig eff Bkg rej comp (area = %0.2f)' % roc_comp_auc)
-plt.plot(roc_full[:,1], 1.-roc_full[:,0], label='Sig eff Bkg rej full train (area = %0.2f)' % roc_full_auc)
-plt.plot(roc_truth[:,1],1.-roc_truth[:,0], label='Sig eff Bkg rej full truth (area = %0.2f)' % roc_truth_auc)
-plt.xlim([0.0, 1.0])
-plt.ylim([0.0, 1.05])
-plt.xlabel('Signal Efficiency')
-plt.ylabel('Background Rejection')
-plt.title('Signal eff-Background rej curves Likelihood ratios of mlp')
-plt.legend(loc="lower right")
-plt.savefig('../plots/full_comparison_mlp_sigbkg.png')
-plt.clf()
-# Multiple plot for all pair-wise ratios
-c_f1_f0_train = np.loadtxt('../plots/mlp/results/dec_train_f1_f0_mlp_ratio_trained.txt')
-c_f1_f0_truth = np.loadtxt('../plots/mlp/results/dec_train_f1_f0_mlp_ratio_truth.txt')
-c_f2_f0_train = np.loadtxt('../plots/mlp/results/dec_train_f2_f0_mlp_ratio_trained.txt')
-c_f2_f0_truth = np.loadtxt('../plots/mlp/results/dec_train_f2_f0_mlp_ratio_truth.txt')
-c_f2_f1_train = np.loadtxt('../plots/mlp/results/dec_train_f2_f1_mlp_ratio_trained.txt')
-c_f2_f1_truth = np.loadtxt('../plots/mlp/results/dec_train_f2_f1_mlp_ratio_truth.txt')
-plt.subplot(311)
-plt.plot(x, c_f1_f0_train, label="Trained")
-plt.plot(x, c_f1_f0_truth, label="Truth")
-plt.xlabel('x')
-plt.ylabel('LR')
-plt.title('Ratio f1-f0')
-plt.legend()
-plt.subplot(312)
-plt.plot(x, c_f2_f0_train, label="Trained")
-plt.plot(x, c_f2_f0_truth, label="Truth")
-plt.xlabel('x')
-plt.ylabel('LR')
-plt.title('Ratio f2-f0')
-plt.legend()
-plt.subplot(313)
-plt.plot(x, c_f2_f1_train, label="Trained")
-plt.plot(x, c_f2_f1_truth, label="Truth")
-plt.xlabel('x')
-plt.ylabel('LR')
-plt.title('Ratio f2-f1')
-plt.legend()
-plt.savefig('../plots/dec_comparison_mlp_ratio.png')
-plt.clf()
-# Multiple plot for all pair-wise ROC
-c_f1_f0_train_roc = np.loadtxt('../plots/mlp/results/dec_train_f1_f0_mlp_roc.txt')
-c_f1_f0_truth_roc = np.loadtxt('../plots/mlp/results/dec_truth_f1_f0_mlp_roc.txt')
-c_f2_f0_train_roc = np.loadtxt('../plots/mlp/results/dec_train_f2_f0_mlp_roc.txt')
-c_f2_f0_truth_roc = np.loadtxt('../plots/mlp/results/dec_truth_f2_f0_mlp_roc.txt')
-c_f2_f1_train_roc = np.loadtxt('../plots/mlp/results/dec_train_f2_f1_mlp_roc.txt')
-c_f2_f1_truth_roc = np.loadtxt('../plots/mlp/results/dec_truth_f2_f1_mlp_roc.txt')
-roc_f1_f0_train_auc = auc(c_f1_f0_train_roc[:,0],c_f1_f0_train_roc[:,1])
-roc_f1_f0_truth_auc = auc(c_f1_f0_truth_roc[:,0],c_f1_f0_truth_roc[:,1])
-roc_f2_f0_train_auc = auc(c_f2_f0_train_roc[:,0],c_f2_f0_train_roc[:,1])
-roc_f2_f0_truth_auc = auc(c_f2_f0_truth_roc[:,0],c_f2_f0_truth_roc[:,1])
-roc_f2_f1_train_auc = auc(c_f2_f1_train_roc[:,0],c_f2_f1_train_roc[:,1])
-roc_f2_f1_truth_auc = auc(c_f2_f1_truth_roc[:,0],c_f2_f1_truth_roc[:,1])
-
-plt.subplot(311)
-plt.plot(c_f1_f0_train_roc[:,0], c_f1_f0_train_roc[:,1], label='ROC f1-f0 train (area = %0.2f)' % roc_f1_f0_train_auc)
-plt.plot(c_f1_f0_truth_roc[:,0], c_f1_f0_truth_roc[:,1], label='ROC f1-f0 truth (area = %0.2f)' % roc_f1_f0_truth_auc)
-plt.plot([0, 1], [0, 1], 'k--')
-plt.xlim([0.0, 1.0])
-plt.ylim([0.0, 1.05])
-plt.xlabel('False Positive Rate')
-plt.ylabel('True Positive Rate')
-plt.title('ROC curves for Likelihood ratios of f1-f0')
-plt.legend(loc="lower right")
-
-plt.subplot(312)
-plt.plot(c_f2_f0_train_roc[:,0], c_f2_f0_train_roc[:,1], label='ROC f2-f0 train (area = %0.2f)' % roc_f2_f0_train_auc)
-plt.plot(c_f2_f0_truth_roc[:,0], c_f2_f0_truth_roc[:,1], label='ROC f2-f0 truth (area = %0.2f)' % roc_f2_f0_truth_auc)
-plt.plot([0, 1], [0, 1], 'k--')
-plt.xlim([0.0, 1.0])
-plt.ylim([0.0, 1.05])
-plt.xlabel('False Positive Rate')
-plt.ylabel('True Positive Rate')
-plt.title('ROC curves for Likelihood ratios of f2-f0')
-plt.legend(loc="lower right")
-
-plt.subplot(313)
-plt.plot(c_f2_f1_train_roc[:,0], c_f2_f1_train_roc[:,1], label='ROC f2-f1 train (area = %0.2f)' % roc_f2_f1_train_auc)
-plt.plot(c_f2_f1_truth_roc[:,0], c_f2_f1_truth_roc[:,1], label='ROC f2-f1 truth (area = %0.2f)' % roc_f2_f1_truth_auc)
-plt.plot([0, 1], [0, 1], 'k--')
-plt.xlim([0.0, 1.0])
-plt.ylim([0.0, 1.05])
-plt.xlabel('False Positive Rate')
-plt.ylabel('True Positive Rate')
-plt.title('ROC curves for Likelihood ratios of f2-f1')
-plt.legend(loc="lower right")
-plt.savefig('../plots/dec_comparison_mlp_roc.png')