diff --git a/peslearn/datagen/configuration_space.py b/peslearn/datagen/configuration_space.py
index 2382202..93cb57f 100644
--- a/peslearn/datagen/configuration_space.py
+++ b/peslearn/datagen/configuration_space.py
@@ -138,7 +138,6 @@ def too_close(self, tooclose=0.1):
         Check to ensure no interatomic distances are too close.
         """
         start = timeit.default_timer()
-        print("Removing geometries with atoms that are too close...")
         nrows_before = len(self.all_geometries.index)
         df = self.all_geometries.copy()
         df = df.round(10)
diff --git a/peslearn/input_processor.py b/peslearn/input_processor.py
index cf22f18..842b04f 100644
--- a/peslearn/input_processor.py
+++ b/peslearn/input_processor.py
@@ -75,7 +75,7 @@ def get_keywords(self):
                            'schema_units' : 'angstrom',      # 'bohr'
                            'sort_pes': 'true',               #'false'
                            'training_points': None,          # any int
-                           'tooclose': 0.1,                  # any int or None
+                           'tooclose': 0.1,                  # any int
                            'use_pips': 'true',               #'false'
                            'validation_points': None         # any int
                             }
diff --git a/peslearn/ml/kernel_ridge_reg.py b/peslearn/ml/kernel_ridge_reg.py
index 214c4cb..6ba74af 100644
--- a/peslearn/ml/kernel_ridge_reg.py
+++ b/peslearn/ml/kernel_ridge_reg.py
@@ -72,7 +72,7 @@ def set_default_hyperparameters(self):
                     if 'polynomial' in kernels or 'poly' in kernels:
                         print("WARNING: Polynomial type kernels are included in this hyperoptimization.")
                         print("\t It is strongly cautioned against optimizing polynomial kernels in a precomputed kernel along with other types of kernels.")
-                        print("\t See KRR docs for more info.")
+                        print("\t See KRR example docs for more info.")
                         # add link to docs?
                     if 'degree' in precomputed_kernel:
                         degrees = np.asarray(precomputed_kernel['degree'])