def dataset(dataset, model_type): ''' This method saves each dataset element (independent variable value) into the sql database. ''' # variables list_error = [] # save dataset for data in dataset: for select_data in data['premodel_dataset']: db_save = Save_Feature({ 'premodel_dataset': select_data, 'id_entity': data['id_entity'], }) # save dataset element, append error(s) db_return = db_save.save_feature(model_type) if db_return['error']: list_error.append(db_return['error']) # return return {'error': list_error}
def feature_count(dataset): '''@feature_count This method saves the number of features that can be expected in a given observation with respect to 'id_entity'. @dataset, we assume that validation has occurred, and safe to assume the data associated with the first dataset instance is identical to any instance n within the overall collection of dataset(s). @dataset['count_features'], is defined within the 'dataset_to_dict' method. Note: this method needs to execute after 'dataset_to_dict' ''' db_save = Save_Feature({ 'id_entity': dataset['id_entity'], 'count_features': dataset['count_features'] }) # save dataset element, append error(s) db_return = db_save.save_count() if db_return['error']: return {'error': db_return['error']} else: return {'error': None}
def feature_count(dataset): ''' This method saves the number of features that can be expected in a given observation with respect to 'id_entity'. @dataset, we assume that validation has occurred, and safe to assume the data associated with the first dataset instance is identical to any instance n within the overall collection of dataset(s). @dataset['count_features'], is defined within the 'dataset_to_dict' method. Note: this method needs to execute after 'dataset_to_dict' ''' db_save = Save_Feature({ 'id_entity': dataset['id_entity'], 'count_features': dataset['count_features'] }) # save dataset element, append error(s) db_return = db_save.save_count() if db_return['error']: return {'error': db_return['error']} else: return {'error': None}
def save_feature_count(self): '''@save_feature_count This method saves the number of features that can be expected in a given observation with respect to 'id_entity'. @self.dataset[0], we assume that validation has occurred, and safe to assume the data associated with the first dataset instance is identical to any instance n within the overall collection of dataset(s). @self.dataset['count_features'], is defined within the 'dataset_to_dict' method. Note: this method needs to execute after 'dataset_to_dict' ''' premodel_data = self.dataset[0] db_save = Save_Feature({ 'id_entity': premodel_data['id_entity'], 'count_features': premodel_data['count_features'] }) # save dataset element, append error(s) db_return = db_save.save_count() if db_return['error']: self.list_error.append(db_return['error'])
def save_svm_info(self): """@save_svm_info This method saves the number of features that can be expected in a given observation with respect to 'id_entity'. @self.dataset[0], we assume that validation has occurred, and safe to assume the data associated with the first dataset instance is identical to any instance n within the overall collection of dataset(s). @self.dataset['count_features'], is defined within the 'dataset_to_dict' method. Note: this method needs to execute after 'dataset_to_dict' """ svm_data = self.dataset[0] db_save = Save_Feature({ 'id_entity': svm_data['id_entity'], 'count_features': svm_data['count_features'] }) # save dataset element, append error(s) db_return = db_save.save_count() if db_return['error']: self.list_error.append(db_return['error'])
def save_svm_info(self): svm_data = self.dataset[0] db_save = Save_Feature({'id_entity': svm_data['id_entity'], 'count_features': svm_data['count_features']}) # save dataset element, append error(s) db_return = db_save.save_count() if db_return['error']: self.list_error.append(db_return['error'])
def save_svm_dataset(self): for data in self.dataset: for dataset in data['svm_dataset']: db_save = Save_Feature({'svm_dataset': dataset, 'id_entity': data['id_entity']}) # save dataset element, append error(s) db_return = db_save.save_feature() if db_return['error']: self.list_error.append(db_return['error'])
def save_premodel_dataset(self): '''@save_premodel_dataset This method saves each dataset element (independent variable value) into the sql database. ''' for data in self.dataset: for dataset in data['premodel_dataset']: db_save = Save_Feature({ 'premodel_dataset': dataset, 'id_entity': data['id_entity'] }) # save dataset element, append error(s) db_return = db_save.save_feature() if db_return['error']: self.list_error.append(db_return['error'])
def save_svm_dataset(self): """@save_svm_dataset This method saves each dataset element (independent variable value) into the sql database. """ for data in self.dataset: for dataset in data['svm_dataset']: db_save = Save_Feature({ 'svm_dataset': dataset, 'id_entity': data['id_entity'] }) # save dataset element, append error(s) db_return = db_save.save_feature() if db_return['error']: self.list_error.append(db_return['error'])