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)