ml.rf

Functions for the random forest classifier.

Functions

evaluate(rf_cls, data_split, mimos)	Evaluate the random forest classifiers and return confusion matrices for both features.
format_plots()	General plotting parameters for the Kulik Lab.
hyperparam_opt(data_split_type, include_esp, ...)
load_data(mimos, include_esp, data_loc)	Load data from CSV files for each mimo in the given list.
plot_confusion_matrices(cms, mimos)	Plot confusion matrices for distance and charge features.
plot_data(df_charge, df_dist, mimos)	Plot the average charge and distance data for the given MIMO types.
plot_gini_importance(rf_cls, df_dist, df_charge)	Plot Gini importance bar plots for the top 20 features for each feature type.
plot_roc_curve(y_true, y_pred_proba, mimos, ...)	Plot the ROC curve for the test data of the charge and distance features.
preprocess_data(df_charge, df_dist, mimos, ...)	Preprocess data for training and testing by splitting it based on the given test fraction.
rf_analysis(data_split_type, include_esp, ...)
train_random_forest(feature, data_split, ...)	Train random forest classifiers for the distance and charge features.
train_random_forest_with_optimization(...)