def main(): ctrl = Controller() ctrl.load_dataset_from_file(DATASET_FILE_PATH) # load model model_name = 'bhmm' ctrl.load_model(MODEL_FILE_PATH, model_name) ctrl.create_model_agnostics(model_name) hm = ctrl.get_model(model_name)._obs_lbl_hashmap file_path = MODEL_FOLDER_PATH + '/' + MODEL_NAME + '.lime_sleeping.png' file_paths = [file_path] labels_to_explain=['sleeping'] import numpy as np # typical for activation pattern for sleeping raw_feature_sleeping = np.array( [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1], dtype=bool) ch_feature_sleeping = np.array( [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=bool) lf_feature_sleeping = np.array( [0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], dtype=bool) data = ctrl._dataset # type: _Dataset ctrl.plot_and_save_explanation( model_name, ch_feature_sleeping, labels_to_explain, file_paths )
def main(): ctrl = Controller() ctrl.load_dataset_from_file(DATASET_FILE_PATH) # load model model_name = 'bhmm' ctrl.load_model(MODEL_FILE_PATH, model_name) ctrl.create_model_agnostics(model_name) file_path = MODEL_FOLDER_PATH + '/' + MODEL_NAME + '.feature_importance.png' ctrl.save_plot_feature_importance(model_name, file_path)