Merge pull request #617 from KnowledgeCaptureAndDiscovery/dev

Preparing for 0.9.5 (classifiers re-trained)
KnowledgeCaptureAndDiscovery · Jan 12, 2024 · 1f5b100 · 1f5b100
2 parents f74c3d8 + b01f09c
commit 1f5b100
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diff --git a/experiments/create_models.py b/experiments/create_models.py
@@ -40,11 +40,11 @@
     'tfdtc': make_pipeline(CountVectorizer(), DecisionTreeClassifier()),
     'tflr': make_pipeline(TfidfVectorizer(), LogisticRegression(solver='liblinear')),
     'tfnb': make_pipeline(TfidfVectorizer(), MultinomialNB()),
-    'tfper': make_pipeline(TfidfVectorizer(), Perceptron(tol=1e-3, random_state=0)),
     'tfrfc': make_pipeline(TfidfVectorizer(), RandomForestClassifier()),  #(max_depth=3, random_state=0))
-    'tfsgd': make_pipeline(TfidfVectorizer(), SGDClassifier(loss='log')),
+    'tfsgd': make_pipeline(TfidfVectorizer(), SGDClassifier(loss='log_loss')),
     'tfxgb': make_pipeline(TfidfVectorizer(), XGBClassifier(use_label_encoder=False,eval_metric="logloss"))
 }
+#'tfper': make_pipeline(TfidfVectorizer(), Perceptron(tol=1e-3, random_state=0)),
 evaluation_names = ('cvlr', 'tflr', 'tfnb', 'cvnb', 'cvbb', 'tfsgd', 'tfxgb', 'tfper', 'tfrfc', 'tfdtc', 'tfada')
 evaluation_text = {
     'cvbb': '"sklearnpipeline(CountVectorizer, BernoulliBayes)", -,Allen,',
@@ -54,21 +54,25 @@
     'tfdtc': '"sklearnpipeline(TFIDFVectorizer, DecisionTreeClassifier)", -,Allen,',
     'tflr': '"sklearnpipeline(TFIDFVectorizer, LogisticRegression)", - ,Allen,',
     'tfnb': '"sklearnpipeline(TFIDFVectorizer, NaiveBayes)", - ,Allen,',
-    'tfper': '"sklearnpipeline(TFIDFVectorizer, Perceptron)", -,Allen,',
     'tfrfc': '"sklearnpipeline(TFIDFVectorizer, RandomForestClassifier)", -,Allen,',
     'tfsgd': '"sklearnpipeline(TFIDFVectorizer, StochasticGradientDescent)",loss = \'log\',Allen,',
     'tfxgb': '"sklearnpipeline(TFIDFVectorizer, XGBClassifier)", -,Allen,'
 }
+#'tfper': '"sklearnpipeline(TFIDFVectorizer, Perceptron)", -,Allen,',
 
 def evaluate_category(corpora,category):
     dec = 3
     cv = StratifiedKFold(n_splits = 5, shuffle=True)
-    file_content = "sklearn Primitive - Citation,Hyperparameters,Input Data Used,Accuracy,Precision,Recall,F-measure,Pickle ID"
+    file_content = f"sklearn Primitive - {category},Hyperparameters,Input Data Used,Accuracy,Precision,Recall,F-measure,Pickle ID"
     limit =  0.0
     file_to_copy = ""
     for name in evaluation_text:
         X = corpora[category].excerpt
         Y = corpora[category][category]
+        #print(X)
+        #for e in X:
+        #    print(e)
+        #Y = Y.astype(int)
         x_train, x_test, y_train, y_test = train_test_split(X, Y, stratify=Y, test_size=0.2)
         pipeline = pipelines[name]
         pipeline.fit(x_train, y_train)

diff --git a/experiments/header_analysis/header_evaluation/header_evaluation_predicted_2024-01-12.csv b/experiments/header_analysis/header_evaluation/header_evaluation_predicted_2024-01-12.csv
diff --git a/experiments/header_analysis/header_evaluation/header_evaluation_summary_2024-01-12.csv b/experiments/header_analysis/header_evaluation/header_evaluation_summary_2024-01-12.csv
@@ -0,0 +1,15 @@
+category,total correct,total incorrect,total missed,precision,recall
+citation,33,7,3,0.825,0.917
+run,20,3,1,0.870,0.952
+install,72,16,10,0.818,0.878
+download,2,3,0,0.400,1.000
+requirements,29,2,2,0.935,0.935
+contact,1,0,2,1.000,0.333
+description,13,5,7,0.722,0.650
+contributor,3,0,0,1.000,1.000
+documentation,18,2,0,0.900,1.000
+license,30,0,0,1.000,1.000
+usage,55,32,20,0.632,0.733
+faq,3,6,2,0.333,0.600
+support,6,8,3,0.429,0.667
+ack,7,0,3,1.000,0.700
diff --git a/...eader_evaluation_predicted_2021-03-10.csv → ...eader_evaluation_predicted_2021-03-10.csv b/...eader_evaluation_predicted_2021-03-10.csv → ...eader_evaluation_predicted_2021-03-10.csv
diff --git a/.../header_evaluation_summary_2021-03-10.csv → .../header_evaluation_summary_2021-03-10.csv b/.../header_evaluation_summary_2021-03-10.csv → .../header_evaluation_summary_2021-03-10.csv
diff --git a/experiments/Classifier Pipelines.ipynb → ...ld_experiments/Classifier Pipelines.ipynb b/experiments/Classifier Pipelines.ipynb → ...ld_experiments/Classifier Pipelines.ipynb
diff --git a/experiments/TFidf-Logistic.ipynb → ...ents/old_experiments/TFidf-Logistic.ipynb b/experiments/TFidf-Logistic.ipynb → ...ents/old_experiments/TFidf-Logistic.ipynb
diff --git a/experiments/TFidf-NB.ipynb → experiments/old_experiments/TFidf-NB.ipynb b/experiments/TFidf-NB.ipynb → experiments/old_experiments/TFidf-NB.ipynb
diff --git a/experiments/helper_scripts/environment.yml → ...xperiments/helper_scripts/environment.yml b/experiments/helper_scripts/environment.yml → ...xperiments/helper_scripts/environment.yml
diff --git a/...nts/helper_scripts/fetchgithubmetadata.py → ...nts/helper_scripts/fetchgithubmetadata.py b/...nts/helper_scripts/fetchgithubmetadata.py → ...nts/helper_scripts/fetchgithubmetadata.py
diff --git a/...ments/helper_scripts/githubrepo2readme.py → ...ments/helper_scripts/githubrepo2readme.py b/...ments/helper_scripts/githubrepo2readme.py → ...ments/helper_scripts/githubrepo2readme.py
diff --git a/experiments/helper_scripts/gitmydoc.py → ...ld_experiments/helper_scripts/gitmydoc.py b/experiments/helper_scripts/gitmydoc.py → ...ld_experiments/helper_scripts/gitmydoc.py
diff --git a/...per_scripts/minegithubrepodescriptions.py → ...per_scripts/minegithubrepodescriptions.py b/...per_scripts/minegithubrepodescriptions.py → ...per_scripts/minegithubrepodescriptions.py
diff --git a/...iments/helper_scripts/printprogressbar.py → ...iments/helper_scripts/printprogressbar.py b/...iments/helper_scripts/printprogressbar.py → ...iments/helper_scripts/printprogressbar.py
diff --git a/...iments/helper_scripts/splitcsvcategory.py → ...iments/helper_scripts/splitcsvcategory.py b/...iments/helper_scripts/splitcsvcategory.py → ...iments/helper_scripts/splitcsvcategory.py
diff --git a/experiments/helper_scripts/synthRepoData.py → ...periments/helper_scripts/synthRepoData.py b/experiments/helper_scripts/synthRepoData.py → ...periments/helper_scripts/synthRepoData.py
diff --git a/experiments/initial_baseline.ipynb → ...ts/old_experiments/initial_baseline.ipynb b/experiments/initial_baseline.ipynb → ...ts/old_experiments/initial_baseline.ipynb
diff --git a/experiments/training_allen/testing.py → ...old_experiments/training_allen/testing.py b/experiments/training_allen/testing.py → ...old_experiments/training_allen/testing.py
diff --git a/experiments/training_allen/training.py → ...ld_experiments/training_allen/training.py b/experiments/training_allen/training.py → ...ld_experiments/training_allen/training.py
diff --git a/experiments/ranking/citation_classifier.csv b/experiments/ranking/citation_classifier.csv
@@ -1,12 +1,12 @@
-sklearn Primitive - Citation,Hyperparameters,Input Data Used,Accuracy,Precision,Recall,F-measure,Pickle ID
-"sklearnpipeline(CountVectorizer, BernoulliBayes)", -,Allen,0.732,0.687,0.984,0.808,citcvbb.p
-"sklearnpipeline(CountVectorizer, LogisticRegression)", - ,Allen,0.877,0.838,0.975,0.901,citcvlr.p
-"sklearnpipeline(CountVectorizer, NaiveBayes)", -,Allen,0.917,0.913,0.946,0.929,citcvnb.p
-"sklearnpipeline(TFIDFVectorizer, AdaBoostClassifier)", -,Allen,0.828,0.913,0.785,0.837,cittfada.p
-"sklearnpipeline(TFIDFVectorizer, DecisionTreeClassifier)", -,Allen,0.792,0.77,0.908,0.833,cittfdtc.p
-"sklearnpipeline(TFIDFVectorizer, LogisticRegression)", - ,Allen,0.875,0.837,0.971,0.899,cittflr.p
-"sklearnpipeline(TFIDFVectorizer, NaiveBayes)", - ,Allen,0.904,0.869,0.981,0.921,cittfnb.p
-"sklearnpipeline(TFIDFVectorizer, Perceptron)", -,Allen,0.884,0.868,0.94,0.902,cittfper.p
-"sklearnpipeline(TFIDFVectorizer, RandomForestClassifier)", -,Allen,0.814,0.782,0.937,0.852,cittfrfc.p
-"sklearnpipeline(TFIDFVectorizer, StochasticGradientDescent)",loss = 'log',Allen,0.895,0.863,0.972,0.914,cittfsgd.p
-"sklearnpipeline(TFIDFVectorizer, XGBClassifier)", -,Allen,0.783,0.783,0.867,0.817,cittfxgb.p
+sklearn Primitive - citation,Hyperparameters,Input Data Used,Accuracy,Precision,Recall,F-measure,Pickle ID
+"sklearnpipeline(CountVectorizer, BernoulliBayes)", -,Allen,0.754,0.675,0.993,0.803,citcvbb.p
+"sklearnpipeline(CountVectorizer, LogisticRegression)", - ,Allen,0.922,0.912,0.938,0.924,citcvlr.p
+"sklearnpipeline(CountVectorizer, NaiveBayes)", -,Allen,0.927,0.909,0.952,0.929,citcvnb.p
+"sklearnpipeline(TFIDFVectorizer, AdaBoostClassifier)", -,Allen,0.886,0.948,0.821,0.877,cittfada.p
+"sklearnpipeline(TFIDFVectorizer, DecisionTreeClassifier)", -,Allen,0.879,0.95,0.8,0.868,cittfdtc.p
+"sklearnpipeline(TFIDFVectorizer, LogisticRegression)", - ,Allen,0.938,0.958,0.917,0.936,cittflr.p
+"sklearnpipeline(TFIDFVectorizer, NaiveBayes)", - ,Allen,0.92,0.91,0.934,0.922,cittfnb.p
+"sklearnpipeline(TFIDFVectorizer, Perceptron)", -,Allen,0.907,0.899,0.921,0.909,cittfper.p
+"sklearnpipeline(TFIDFVectorizer, RandomForestClassifier)", -,Allen,0.879,0.864,0.907,0.882,cittfrfc.p
+"sklearnpipeline(TFIDFVectorizer, StochasticGradientDescent)",loss = 'log',Allen,0.939,0.957,0.921,0.938,cittfsgd.p
+"sklearnpipeline(TFIDFVectorizer, XGBClassifier)", -,Allen,0.839,0.906,0.759,0.825,cittfxgb.p
diff --git a/experiments/ranking/description_classifier.csv b/experiments/ranking/description_classifier.csv
@@ -1,12 +1,12 @@
-sklearn Primitive - Citation,Hyperparameters,Input Data Used,Accuracy,Precision,Recall,F-measure,Pickle ID
-"sklearnpipeline(CountVectorizer, BernoulliBayes)", -,Allen,0.725,0.934,0.559,0.699,descvbb.p
-"sklearnpipeline(CountVectorizer, LogisticRegression)", - ,Allen,0.818,0.876,0.795,0.833,descvlr.p
-"sklearnpipeline(CountVectorizer, NaiveBayes)", -,Allen,0.816,0.776,0.955,0.856,descvnb.p
-"sklearnpipeline(TFIDFVectorizer, AdaBoostClassifier)", -,Allen,0.798,0.838,0.8,0.818,destfada.p
-"sklearnpipeline(TFIDFVectorizer, DecisionTreeClassifier)", -,Allen,0.767,0.823,0.759,0.787,destfdtc.p
-"sklearnpipeline(TFIDFVectorizer, LogisticRegression)", - ,Allen,0.827,0.802,0.926,0.859,destflr.p
-"sklearnpipeline(TFIDFVectorizer, NaiveBayes)", - ,Allen,0.779,0.728,0.982,0.836,destfnb.p
-"sklearnpipeline(TFIDFVectorizer, Perceptron)", -,Allen,0.826,0.853,0.842,0.847,destfper.p
-"sklearnpipeline(TFIDFVectorizer, RandomForestClassifier)", -,Allen,0.784,0.83,0.783,0.805,destfrfc.p
-"sklearnpipeline(TFIDFVectorizer, StochasticGradientDescent)",loss = 'log',Allen,0.847,0.875,0.857,0.865,destfsgd.p
-"sklearnpipeline(TFIDFVectorizer, XGBClassifier)", -,Allen,0.76,0.806,0.768,0.786,destfxgb.p
+sklearn Primitive - description,Hyperparameters,Input Data Used,Accuracy,Precision,Recall,F-measure,Pickle ID
+"sklearnpipeline(CountVectorizer, BernoulliBayes)", -,Allen,0.733,0.914,0.516,0.657,descvbb.p
+"sklearnpipeline(CountVectorizer, LogisticRegression)", - ,Allen,0.813,0.854,0.758,0.801,descvlr.p
+"sklearnpipeline(CountVectorizer, NaiveBayes)", -,Allen,0.784,0.716,0.954,0.816,descvnb.p
+"sklearnpipeline(TFIDFVectorizer, AdaBoostClassifier)", -,Allen,0.731,0.73,0.737,0.733,destfada.p
+"sklearnpipeline(TFIDFVectorizer, DecisionTreeClassifier)", -,Allen,0.686,0.701,0.648,0.67,destfdtc.p
+"sklearnpipeline(TFIDFVectorizer, LogisticRegression)", - ,Allen,0.802,0.788,0.836,0.809,destflr.p
+"sklearnpipeline(TFIDFVectorizer, NaiveBayes)", - ,Allen,0.775,0.695,0.982,0.814,destfnb.p
+"sklearnpipeline(TFIDFVectorizer, Perceptron)", -,Allen,0.804,0.777,0.854,0.814,destfper.p
+"sklearnpipeline(TFIDFVectorizer, RandomForestClassifier)", -,Allen,0.745,0.744,0.751,0.747,destfrfc.p
+"sklearnpipeline(TFIDFVectorizer, StochasticGradientDescent)",loss = 'log',Allen,0.815,0.799,0.843,0.82,destfsgd.p
+"sklearnpipeline(TFIDFVectorizer, XGBClassifier)", -,Allen,0.72,0.729,0.726,0.724,destfxgb.p
diff --git a/experiments/ranking/installation_classifier.csv b/experiments/ranking/installation_classifier.csv
@@ -1,12 +1,12 @@
-sklearn Primitive - Citation,Hyperparameters,Input Data Used,Accuracy,Precision,Recall,F-measure,Pickle ID
-"sklearnpipeline(CountVectorizer, BernoulliBayes)", -,Allen,0.75,0.7,0.986,0.819,inscvbb.p
-"sklearnpipeline(CountVectorizer, LogisticRegression)", - ,Allen,0.871,0.87,0.912,0.89,inscvlr.p
-"sklearnpipeline(CountVectorizer, NaiveBayes)", -,Allen,0.879,0.844,0.968,0.902,inscvnb.p
-"sklearnpipeline(TFIDFVectorizer, AdaBoostClassifier)", -,Allen,0.79,0.899,0.714,0.794,instfada.p
-"sklearnpipeline(TFIDFVectorizer, DecisionTreeClassifier)", -,Allen,0.816,0.877,0.789,0.83,instfdtc.p
-"sklearnpipeline(TFIDFVectorizer, LogisticRegression)", - ,Allen,0.894,0.908,0.906,0.907,instflr.p
-"sklearnpipeline(TFIDFVectorizer, NaiveBayes)", - ,Allen,0.842,0.791,0.986,0.877,instfnb.p
-"sklearnpipeline(TFIDFVectorizer, Perceptron)", -,Allen,0.865,0.895,0.864,0.879,instfper.p
-"sklearnpipeline(TFIDFVectorizer, RandomForestClassifier)", -,Allen,0.851,0.9,0.833,0.865,instfrfc.p
-"sklearnpipeline(TFIDFVectorizer, StochasticGradientDescent)",loss = 'log',Allen,0.896,0.918,0.899,0.908,instfsgd.p
-"sklearnpipeline(TFIDFVectorizer, XGBClassifier)", -,Allen,0.812,0.881,0.776,0.825,instfxgb.p
+sklearn Primitive - installation,Hyperparameters,Input Data Used,Accuracy,Precision,Recall,F-measure,Pickle ID
+"sklearnpipeline(CountVectorizer, BernoulliBayes)", -,Allen,0.76,0.678,0.991,0.805,inscvbb.p
+"sklearnpipeline(CountVectorizer, LogisticRegression)", - ,Allen,0.894,0.874,0.923,0.897,inscvlr.p
+"sklearnpipeline(CountVectorizer, NaiveBayes)", -,Allen,0.898,0.853,0.961,0.904,inscvnb.p
+"sklearnpipeline(TFIDFVectorizer, AdaBoostClassifier)", -,Allen,0.797,0.882,0.685,0.771,instfada.p
+"sklearnpipeline(TFIDFVectorizer, DecisionTreeClassifier)", -,Allen,0.825,0.841,0.807,0.822,instfdtc.p
+"sklearnpipeline(TFIDFVectorizer, LogisticRegression)", - ,Allen,0.894,0.938,0.845,0.889,instflr.p
+"sklearnpipeline(TFIDFVectorizer, NaiveBayes)", - ,Allen,0.897,0.851,0.965,0.904,instfnb.p
+"sklearnpipeline(TFIDFVectorizer, Perceptron)", -,Allen,0.887,0.887,0.887,0.887,instfper.p
+"sklearnpipeline(TFIDFVectorizer, RandomForestClassifier)", -,Allen,0.87,0.854,0.894,0.873,instfrfc.p
+"sklearnpipeline(TFIDFVectorizer, StochasticGradientDescent)",loss = 'log',Allen,0.903,0.922,0.882,0.901,instfsgd.p
+"sklearnpipeline(TFIDFVectorizer, XGBClassifier)", -,Allen,0.833,0.874,0.781,0.824,instfxgb.p
diff --git a/experiments/ranking/invocation_classifier.csv b/experiments/ranking/invocation_classifier.csv
@@ -1,12 +1,12 @@
-sklearn Primitive - Citation,Hyperparameters,Input Data Used,Accuracy,Precision,Recall,F-measure,Pickle ID
-"sklearnpipeline(CountVectorizer, BernoulliBayes)", -,Allen,0.754,0.718,0.939,0.814,invcvbb.p
-"sklearnpipeline(CountVectorizer, LogisticRegression)", - ,Allen,0.84,0.817,0.929,0.869,invcvlr.p
-"sklearnpipeline(CountVectorizer, NaiveBayes)", -,Allen,0.865,0.875,0.891,0.883,invcvnb.p
-"sklearnpipeline(TFIDFVectorizer, AdaBoostClassifier)", -,Allen,0.773,0.753,0.899,0.819,invtfada.p
-"sklearnpipeline(TFIDFVectorizer, DecisionTreeClassifier)", -,Allen,0.763,0.847,0.716,0.776,invtfdtc.p
-"sklearnpipeline(TFIDFVectorizer, LogisticRegression)", - ,Allen,0.841,0.822,0.923,0.869,invtflr.p
-"sklearnpipeline(TFIDFVectorizer, NaiveBayes)", - ,Allen,0.869,0.848,0.94,0.892,invtfnb.p
-"sklearnpipeline(TFIDFVectorizer, Perceptron)", -,Allen,0.841,0.862,0.861,0.861,invtfper.p
-"sklearnpipeline(TFIDFVectorizer, RandomForestClassifier)", -,Allen,0.826,0.868,0.82,0.843,invtfrfc.p
-"sklearnpipeline(TFIDFVectorizer, StochasticGradientDescent)",loss = 'log',Allen,0.867,0.859,0.919,0.888,invtfsgd.p
-"sklearnpipeline(TFIDFVectorizer, XGBClassifier)", -,Allen,0.798,0.778,0.907,0.837,invtfxgb.p
+sklearn Primitive - invocation,Hyperparameters,Input Data Used,Accuracy,Precision,Recall,F-measure,Pickle ID
+"sklearnpipeline(CountVectorizer, BernoulliBayes)", -,Allen,0.755,0.681,0.962,0.797,invcvbb.p
+"sklearnpipeline(CountVectorizer, LogisticRegression)", - ,Allen,0.858,0.828,0.907,0.865,invcvlr.p
+"sklearnpipeline(CountVectorizer, NaiveBayes)", -,Allen,0.885,0.874,0.899,0.886,invcvnb.p
+"sklearnpipeline(TFIDFVectorizer, AdaBoostClassifier)", -,Allen,0.771,0.74,0.836,0.785,invtfada.p
+"sklearnpipeline(TFIDFVectorizer, DecisionTreeClassifier)", -,Allen,0.766,0.757,0.784,0.77,invtfdtc.p
+"sklearnpipeline(TFIDFVectorizer, LogisticRegression)", - ,Allen,0.869,0.87,0.868,0.869,invtflr.p
+"sklearnpipeline(TFIDFVectorizer, NaiveBayes)", - ,Allen,0.89,0.878,0.907,0.892,invtfnb.p
+"sklearnpipeline(TFIDFVectorizer, Perceptron)", -,Allen,0.848,0.845,0.853,0.849,invtfper.p
+"sklearnpipeline(TFIDFVectorizer, RandomForestClassifier)", -,Allen,0.823,0.807,0.85,0.827,invtfrfc.p
+"sklearnpipeline(TFIDFVectorizer, StochasticGradientDescent)",loss = 'log',Allen,0.879,0.878,0.881,0.879,invtfsgd.p
+"sklearnpipeline(TFIDFVectorizer, XGBClassifier)", -,Allen,0.803,0.771,0.863,0.815,invtfxgb.p
diff --git a/experiments/setup_corpus.py b/experiments/setup_corpus.py
@@ -18,9 +18,10 @@ def build_corpora():
 def build_corpus(selected_category):
     categories_df = {cat: pd.read_csv(f'./training_corpus/{cat}.csv') for cat in categories}
     negative_sample_size = int(len(categories_df[selected_category]) / 4)
-    print(f"Selected Category: {selected_category}")
+    print(f"Selected Category: {selected_category}. Negative sample size for category: {negative_sample_size}")
     for category in categories_df:
-        categories_df[category].drop('URL', 1, inplace=True)
+        categories_df[category].drop('URL', axis=1, inplace=True)
+        # add negative samples to a category from the other ones
         if category != selected_category:
             categories_df[category] = categories_df[category].sample(negative_sample_size)
         categories_df[category] = categories_df[category].assign(**{selected_category: category == selected_category})
@@ -30,9 +31,13 @@ def build_corpus(selected_category):
         map(lambda sent: ' '.join(sent), random.sample(list(treebank.sents()), negative_sample_size)),
         columns=["excerpt"]).assign(description=False)
     # print("Treebank has {} samples.".format(len(treebank_background)))
-    # print("categories_df")
+    # Rename the column to match the corpus when merging
+    treebank_background = treebank_background.rename(columns={'description': selected_category})
+    # print(categories_df)
     corpus = pd.concat(categories_df.values(), ignore_index=True, sort=False)
-    corpus.append(treebank_background, ignore_index=True, sort=False)
+    #corpus.append(treebank_background, ignore_index=True, sort=False)
+    corpus = pd.concat([corpus, treebank_background], ignore_index=True, sort=False)
     corpus.fillna(value='', inplace=True)
+    # print(corpus)
     return corpus
 
diff --git a/experiments/trained_models/citcvbb.p b/experiments/trained_models/citcvbb.p
diff --git a/experiments/trained_models/citcvlr.p b/experiments/trained_models/citcvlr.p
diff --git a/experiments/trained_models/citcvnb.p b/experiments/trained_models/citcvnb.p
diff --git a/experiments/trained_models/cittfada.p b/experiments/trained_models/cittfada.p
diff --git a/experiments/trained_models/cittfdtc.p b/experiments/trained_models/cittfdtc.p
diff --git a/experiments/trained_models/cittflr.p b/experiments/trained_models/cittflr.p
diff --git a/experiments/trained_models/cittfnb.p b/experiments/trained_models/cittfnb.p
diff --git a/experiments/trained_models/cittfper.p b/experiments/trained_models/cittfper.p
diff --git a/experiments/trained_models/cittfrfc.p b/experiments/trained_models/cittfrfc.p
diff --git a/experiments/trained_models/cittfsgd.p b/experiments/trained_models/cittfsgd.p
diff --git a/experiments/trained_models/cittfxgb.p b/experiments/trained_models/cittfxgb.p
diff --git a/experiments/trained_models/descvbb.p b/experiments/trained_models/descvbb.p
diff --git a/experiments/trained_models/descvlr.p b/experiments/trained_models/descvlr.p
diff --git a/experiments/trained_models/descvnb.p b/experiments/trained_models/descvnb.p
diff --git a/experiments/trained_models/destfada.p b/experiments/trained_models/destfada.p
diff --git a/experiments/trained_models/destfdtc.p b/experiments/trained_models/destfdtc.p
diff --git a/experiments/trained_models/destflr.p b/experiments/trained_models/destflr.p
diff --git a/experiments/trained_models/destfnb.p b/experiments/trained_models/destfnb.p
diff --git a/experiments/trained_models/destfper.p b/experiments/trained_models/destfper.p
diff --git a/experiments/trained_models/destfrfc.p b/experiments/trained_models/destfrfc.p
diff --git a/experiments/trained_models/destfsgd.p b/experiments/trained_models/destfsgd.p
diff --git a/experiments/trained_models/destfxgb.p b/experiments/trained_models/destfxgb.p
diff --git a/experiments/trained_models/inscvbb.p b/experiments/trained_models/inscvbb.p
diff --git a/experiments/trained_models/inscvlr.p b/experiments/trained_models/inscvlr.p
diff --git a/experiments/trained_models/inscvnb.p b/experiments/trained_models/inscvnb.p
diff --git a/experiments/trained_models/instfada.p b/experiments/trained_models/instfada.p
diff --git a/experiments/trained_models/instfdtc.p b/experiments/trained_models/instfdtc.p
diff --git a/experiments/trained_models/instflr.p b/experiments/trained_models/instflr.p
diff --git a/experiments/trained_models/instfnb.p b/experiments/trained_models/instfnb.p
diff --git a/experiments/trained_models/instfper.p b/experiments/trained_models/instfper.p
diff --git a/experiments/trained_models/instfrfc.p b/experiments/trained_models/instfrfc.p
diff --git a/experiments/trained_models/instfsgd.p b/experiments/trained_models/instfsgd.p
diff --git a/experiments/trained_models/instfxgb.p b/experiments/trained_models/instfxgb.p
diff --git a/experiments/trained_models/invcvbb.p b/experiments/trained_models/invcvbb.p
diff --git a/experiments/trained_models/invcvlr.p b/experiments/trained_models/invcvlr.p
diff --git a/experiments/trained_models/invcvnb.p b/experiments/trained_models/invcvnb.p
diff --git a/experiments/trained_models/invtfada.p b/experiments/trained_models/invtfada.p
diff --git a/experiments/trained_models/invtfdtc.p b/experiments/trained_models/invtfdtc.p
diff --git a/experiments/trained_models/invtflr.p b/experiments/trained_models/invtflr.p
diff --git a/experiments/trained_models/invtfnb.p b/experiments/trained_models/invtfnb.p
diff --git a/experiments/trained_models/invtfper.p b/experiments/trained_models/invtfper.p
diff --git a/experiments/trained_models/invtfrfc.p b/experiments/trained_models/invtfrfc.p
diff --git a/experiments/trained_models/invtfsgd.p b/experiments/trained_models/invtfsgd.p
diff --git a/experiments/trained_models/invtfxgb.p b/experiments/trained_models/invtfxgb.p