Modify README.md

README.md

@@ -29,12 +29,10 @@ The dataset is derived from the DBPP GitHub repository (https://github.com/yxgu2
 All molecules were standardized using MolVS(clean_data.py), the datasets were split by sklearn(split_dataset.py), and RDKit descriptors (216 features) were computed (Rdkit_descriptor.py).
 
 ### Files:
-- 'train.parquet': Raw training set (SMILES + labels)
-- 'test.parquet': Raw test set (SMILES + labels)
-- 'train_rdkit_descriptors.parquet': RDKit descriptors for training data
-- 'test_rdkit_descriptors.parquet': RDKit descriptors for test data
+- 'train_rdkit_descriptors.parquet'
+- 'test_rdkit_descriptors.parquet'
 
-Each descriptor file contains:
+Each file contains:
 - 'label': 0 for non-drug, 1 for drug
 - 'Standardized_SMILES'
 - 216 numerical RDKit descriptors
@@ -42,6 +40,3 @@ Each descriptor file contains:
 ## Model Development
 
 All models were trained using H2O AutoML with 10-fold cross-validation(model_constrcution.py). The top 3 models were also evaluated using an independent test set, and SHAP analysis was used to interpret the top structural features contributing to drug-likeness(model_analysis.py).
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