def prediction(cls, name: str, request_data: Dict[str, Any]):
try:
brain = cls.load_brain(name)
request_data = DatasetPreprocessing.add_time_information(
request_data)
data = pd.DataFrame([request_data])
prepared_data = DatasetPreprocessing.prepare_prediction(
brain, data)
prediction = brain.estimator().predict(prepared_data)
if (brain.configuration.dependent_encode
and brain.configuration.estimator.typed
== BrainEstimatorType.CLASSIFIER):
prediction = brain.dataset.dependent_encoder.inverse_transform(
prediction)
prediction = list(map(bool, prediction))
else:
prediction = list(map(float, prediction))
return BrainPredictionResult(
brain=brain.info,
preprocessed=prepared_data.head(1).to_dict('records')[0],
prediction=prediction[0])
except FileNotFoundError as exc:
raise BrainNotTrained(name) from exc
except Exception as exc: # pylint: disable=broad-except
logger.exception(exc)
raise LearningHouseException() from exc
def get_brain(name: str) -> BrainConfiguration:
try:
return BrainConfiguration.from_json_file(name)
except FileNotFoundError as exc:
raise BrainNoConfiguration(name) from exc
except Exception as exc: # pylint: disable=broad-except
logger.exception(exc)
raise LearningHouseException() from exc
def train(name: str, data: pd.DataFrame) -> BrainInfo:
try:
brain = Brain(name)
if len(data.index) < 10:
raise BrainNotEnoughData()
brain, x_train, x_test, y_train, y_test = DatasetPreprocessing.prepare_training(
brain, data, False)
estimator = brain.estimator()
selector = SelectFromModel(estimator)
selector.fit(x_train, y_train)
brain.dataset.features = x_train.columns[(
selector.get_support())].values.tolist()
brain, x_train, x_test, y_train, y_test = DatasetPreprocessing.prepare_training(
brain, data, True)
estimator.fit(x_train, y_train)
if BrainEstimatorType.CLASSIFIER == brain.configuration.estimator.typed:
y_pred = estimator.predict(x_test)
score = accuracy_score(y_test, y_pred)
else:
score = estimator.score(x_test, y_test)
brain.store_trained(x_train.columns.tolist(), len(data.index),
score)
return brain.info
except FileNotFoundError as exc:
raise BrainNoConfiguration(name) from exc
except Exception as exc: # pylint: disable=broad-except
logger.exception(exc)
raise LearningHouseException() from exc