Classification and Oversampling Algorithms Comparison, using Deep Feature Synthesis and Feature Selection with RFE
CatBoost Model Pipeline
1-Imputer
2-Encoder
3-Scaler
3-Balancer with SvmSmote
4-Feature Genarator with FeatureTools using Deep Feature Synthesis
5-Feature Selector with RFE
6-HyperParameter Tuning with Bayesian Optimization
7-Cross Validation with K-Fold Cross Validation
CatBoost Model with Oversampled Data With Svmsmote - hGBM Model With Oversampled Data With Kmeanssmote
Comparison of Hyper Parameters optimized Models
