return F.analyse_dataset(ds)
def get_model_data(self, name, db_fix=True):
predictor_record = Predictor.query.filter_by(company_id=self.company_id, name=name)model = predictor_record.data
// Make some corrections for databases not to break when dealing with empty columns
if db_fix:
After Change
return F.analyse_dataset(ds)
def get_model_data(self, name, db_fix=True):
predictor_record = Predictor.query.filter_by(company_id=self.company_id, name=name).first()model = predictor_record.data
if model is None or model["status"] == "training":
self.fs_store.get(name, f"predictor_{self.company_id}_{name}", self.config["paths"]["predictors"])
model = mindsdb_native.F.get_model_data(name)
