Kaggle Website: https://www.kaggle.com/wenruliu/adult-income-dataset
#1 result of preprocessing
#2 result of encoding&scaling
ex) ordinal encoding & standardization scaling
#3 result of classification
#3-1 Ordinal encoding & standardization scaling
Best : Logistic Regression {'C': 1.0, 'max_iter': 1000, 'multi_class': 'auto', 'penalty': 'l1', 'random_state': 3, 'solver': 'saga'} -0.22446976715459205
#3-2 Ordinal encoding & MinMax scaling
Best : Logistic Regression {'C': 1.0, 'max_iter': 1000, 'multi_class': 'auto', 'penalty': 'l1', 'random_state': 3, 'solver': 'saga'} -0.22446976715459205
#3-3 Ordinal encoding & MaxAbs scaling
Best : Logistic Regression {'C': 1.0, 'max_iter': 1000, 'multi_class': 'auto', 'penalty': 'l1', 'random_state': 3, 'solver': 'saga'} -0.22446976715459205
#3-4 Ordinal encoding & Robust scaling
Best : Logistic Regression {'C': 1.0, 'max_iter': 1000, 'multi_class': 'auto', 'penalty': 'l1', 'random_state': 3, 'solver': 'saga'} -0.22446976715459205
#3-5 OneHot encoding & standardization scaling
Best : Logistic Regression {'C': 1.0, 'max_iter': 1000, 'multi_class': 'auto', 'penalty': 'l1', 'random_state': 3, 'solver': 'saga'} -0.22446976715459205
#3-6 OneHot encoding & MinMax scaling
Best : Logistic Regression {'C': 1.0, 'max_iter': 1000, 'multi_class': 'auto', 'penalty': 'l1', 'random_state': 3, 'solver': 'saga'} -0.22446976715459205
#3-7 OneHot encoding & MaxAbs scaling
Best : Decisioin Tree Regressor {'criterion': 'entropy', 'max_depth': 5, 'max_features': 'sqrt', 'min_samples_leaf': 3, 'min_samples_split': 5, 'splitter': 'best'} -0.22324606262738556
#3-6 OneHot encoding & Robust scaling
Best : Logistic Regression {'C': 1.0, 'max_iter': 1000, 'multi_class': 'auto', 'penalty': 'l1', 'random_state': 3, 'solver': 'saga'} -0.22446976715459205
**** Best Result **** OneHot encoding & MaxAbs scaling with Decision Tree Regressor Accuracy : -0.22324606262738556 parameter {'criterion': 'entropy', 'max_depth': 5, 'max_features': 'sqrt', 'min_samples_leaf': 3, 'min_samples_split': 5, 'splitter': 'best'}