def model_index(features: Optional[bool] = True,
parameters: Optional[bool] = True,
tests: Optional[bool] = True,
query: Optional[dict] = Body(...),
service: ModelService = Depends(ModelService)):
result = {}
if features:
result['features'] = service.clear_features(query)
if parameters:
result['parameters'] = service.clear_parameters(query)
if tests:
result['tests'] = service.clear_tests(query)
return result
def main(dataset: str, target: str):
service = FeatureSelectionService()
models = ModelService()
datasets = DatasetService()
query = {"dataset": dataset, "target": target}
# Clear feature search results from models
models.clear_features(query)
#search_models = models.query_models(query)
# logging.info("[i] {} models for feature selection".format(len(search_models)))
# for i, m in enumerate(search_models):
symbols = datasets.get_dataset_symbols(dataset)
for i, sym in enumerate(symbols):
logging.info("==[{}/{}]== Dataset: {} {} {} =====".format(
i + 1, len(symbols), sym, dataset, target))
mf = service.create_features_search(target=target,
dataset=dataset,
symbol=sym,
split=0.7,
method='importances')
logging.info("[{}] Start feature search".format(get_timestamp()))
mf = service.feature_selection(mf, sync=True)
logging.info("[{}] End feature search".format(get_timestamp()))