labels.append(1) else: labels.append(0) if verbose: # print(data) # print(files) print(labels) print() return data, labels if __name__ == '__main__': train_data, train_target = fetch_data('downgesture_train.list') neuralnet = NeuralNetwork() neuralnet.add_layer(size=1, input_size=len(train_data[0]), type='input') neuralnet.add_layer(size=100) neuralnet.add_layer(size=1, type='output') neuralnet.fit(data=train_data, target=train_target, eta=0.1, verbose=verbose) # if needed clean data # fit a model # train a model test_data, test_target = fetch_data('downgesture_test.list') predicted_target = neuralnet.predict(test_data) accuracy = neuralnet.accuracy(test_target, predicted_target) print("Accuracy:", accuracy)