def _predict(): """予測。""" logger = tk.log.get(__name__) X_test = _data.load_test_data() threshold = float((MODELS_DIR / 'threshold.txt').read_text()) logger.info(f'threshold = {threshold:.3f}') pred_list = predict_all('test', X_test) pred = np.mean(pred_list, axis=0) > threshold _data.save_submission(MODELS_DIR / 'submission.csv', pred)
def _predict(): """予測。""" X_test = _data.load_test_data() pred = predict_all('test', X_test) _data.save_submission(MODELS_DIR / 'submission.csv', pred > 0.50) _data.save_submission(MODELS_DIR / 'submission_0.40.csv', pred > 0.40) _data.save_submission(MODELS_DIR / 'submission_0.45.csv', pred > 0.45) _data.save_submission(MODELS_DIR / 'submission_0.55.csv', pred > 0.55) _data.save_submission(MODELS_DIR / 'submission_0.60.csv', pred > 0.60)
def _predict(): """予測。""" X_test = _data.load_test_data() pred_list = predict_all('test', X_test) pred = np.mean(pred_list, axis=0) > 0.5 _data.save_submission(MODELS_DIR / 'submission.csv', pred)