Update README.md

README.md

@@ -45,7 +45,7 @@ dataset_info:
     dtype: string
   - name: ID
     dtype: int64
-  - name: endpoint
+  - name: Y
     dtype:
       class_label:
         names:
@@ -64,7 +64,7 @@ dataset_info:
   features:
   - name: SMILES
     dtype: string
-  - name: endpoint
+  - name: Y
     dtype: 
       class_label:
         names:
@@ -110,11 +110,11 @@ and inspecting the loaded dataset
     >>> train_test
     DatasetDict({
     train: Dataset({
-        features: ['SMILES', 'ID', 'endpoint', 'MW'],
+        features: ['SMILES', 'ID', 'Y', 'MW'],
         num_rows: 6862
     })
     test: Dataset({
-        features: ['SMILES', 'ID', 'endpoint', 'MW'],
+        features: ['SMILES', 'ID', 'Y', 'MW'],
         num_rows: 1714
     })
     })
@@ -148,7 +148,7 @@ then load, featurize, split, fit, and evaluate the a catboost model
         "name": "cat_boost_classifier",
         "config": {
             "x_features": ['SMILES::morgan', 'SMILES::maccs_rdkit'],
-            "y_features": ['endpoint']}})
+            "y_features": ['Y']}})
     
     model.train(split_featurised_dataset["train"])
     
@@ -157,8 +157,8 @@ then load, featurize, split, fit, and evaluate the a catboost model
     classification_suite = load_suite("classification")
     
     scores = classification_suite.compute(
-        references=split_featurised_dataset["test"]['endpoint'],
-        predictions=preds["cat_boost_classifier::endpoint"])
+        references=split_featurised_dataset["test"]['Y'],
+        predictions=preds["cat_boost_classifier::Y"])
 
 ### Citation