This project is focused on detecting fake profiles using a Decision Tree Regressor. It includes data preprocessing, model training, evaluation, and saving the model for future use.
- Handles missing values using median imputation
- Encodes categorical columns using Label Encoding
- Normalizes numerical features using MinMaxScaler
- Trains a Decision Tree Regressor model
- Evaluates performance using accuracy and classification report
- Saves the trained model using joblib
- File:
profile_Dataset.csv - Contains numerical and categorical features
- Target column:
fake(indicates whether a profile is real or fake)
- Clone the repository:
git clone https://github.com/yourusername/your-repo-name.git cd your-repo-name