This project involves a comparison and analysis of classic methods of linear classification:
- Logistic Regression (LR)
- Support Vector Machines (SVM)
across various parameters. Also implemented are:
- probability calibration for linear classifiers
- different methods for processing categorical data
- feature selection in the model
- assessment of the economic impact of the model depending on various hyperparameters