edamame#
- edamame.eda
- eda
correlation_categorical()correlation_pearson()correlation_phik()describe_distribution()dimensions()drop_columns()handling_missing()identify_types()inspection()interaction()missing()modify_cardinality()num_to_categorical()num_variable_study()plot_categorical()plot_numerical()split_and_scaling()view_cardinality()
- tools
- eda
- edamame.regressor
- diagnose
RegressorDiagnoseRegressorDiagnose.X_trainRegressorDiagnose.y_trainRegressorDiagnose.X_testRegressorDiagnose.y_testRegressorDiagnose.coefficients()RegressorDiagnose.prediction_error()RegressorDiagnose.qqplot()RegressorDiagnose.random_forest_fi()RegressorDiagnose.residual_plot()RegressorDiagnose.xgboost_fi()
check_random_forest()check_xgboost()
- regression
TrainRegressorTrainRegressor.X_trainTrainRegressor.y_trainTrainRegressor.X_testTrainRegressor.y_testTrainRegressor.auto_ml()TrainRegressor.lasso()TrainRegressor.linear()TrainRegressor.model_metrics()TrainRegressor.random_forest()TrainRegressor.ridge()TrainRegressor.save_model()TrainRegressor.tree()TrainRegressor.xgboost()
regression_metrics()
- diagnose
- edamame.classifier
- classification
TrainClassifierTrainClassifier.X_trainTrainClassifier.y_trainTrainClassifier.X_testTrainClassifier.y_testTrainClassifier.auto_ml()TrainClassifier.gaussian_nb()TrainClassifier.knn()TrainClassifier.logistic()TrainClassifier.model_metrics()TrainClassifier.random_forest()TrainClassifier.save_model()TrainClassifier.svm()TrainClassifier.tree()TrainClassifier.xgboost()
classifier_metrics()
- diagnose
- classification