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Data Ingestion :
- In Data Ingestion phase the data is first read as csv.
- Then the data is split into training and testing and saved as csv file.
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Data Transformation :
- In this phase a ColumnTransformer Pipeline is created.
- For Numeric Variables first SimpleImputer is applied with strategy median , then Standard Scaling is performed on numeric data.
- For Categorical Variables SimpleImputer is applied with most frequent strategy, then ordinal encoding performed , after this data is scaled with Stusandard Scaler.
- This preprocessor is saved as pickle file.
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Model Training :
- In this phase base model is tested . The best model found was catboost regressor.
- After this hyperparameter tuning is performed on catboost and knn model.
- A final VotingRegressor is created which will combine prediction of catboost, xgboost and knn models.
- This model is saved as pickle file.
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Prediction Pipeline :
- This pipeline converts given data into dataframe and has various functions to load pickle files and predict the final results in python.
