diff --git a/src/pg/sql/05_segmentation.sql b/src/pg/sql/05_segmentation.sql index aa69bc8..a93f3e8 100644 --- a/src/pg/sql/05_segmentation.sql +++ b/src/pg/sql/05_segmentation.sql @@ -50,12 +50,23 @@ RETURNS TABLE (cartodb_id TEXT, prediction NUMERIC, accuracy NUMERIC) AS $$ from crankshaft.segmentation import Segmentation seg = Segmentation() - model_params = {'n_estimators': n_estimators, 'max_depth':max_depth, 'subsample' : subsample, 'learning_rate': learning_rate, 'min_samples_leaf' : min_samples_leaf} - return seg.create_and_predict_segment(query,variable_name,target_table, model_params) + model_params = { + 'n_estimators': n_estimators, + 'max_depth': max_depth, + 'subsample': subsample, + 'learning_rate': learning_rate, + 'min_samples_leaf': min_samples_leaf + } + return seg.create_and_predict_segment( + query, + variable_name, + target_table, + model_params + ) $$ LANGUAGE plpythonu VOLATILE PARALLEL UNSAFE; CREATE OR REPLACE FUNCTION - CDB_CreateAndPredictSegment ( + CDB_CreateAndPredictSegment( query TEXT, variable TEXT, feature_columns TEXT[], @@ -69,6 +80,18 @@ RETURNS TABLE (cartodb_id TEXT, prediction NUMERIC, accuracy NUMERIC) AS $$ from crankshaft.segmentation import Segmentation seg = Segmentation() - model_params = {'n_estimators': n_estimators, 'max_depth':max_depth, 'subsample' : subsample, 'learning_rate': learning_rate, 'min_samples_leaf' : min_samples_leaf} - return seg.create_and_predict_segment(query, variable, feature_columns, target_query, model_params) + model_params = { + 'n_estimators': n_estimators, + 'max_depth': max_depth, + 'subsample': subsample, + 'learning_rate': learning_rate, + 'min_samples_leaf': min_samples_leaf + } + return seg.create_and_predict_segment( + query, + variable, + feature_columns, + target_query, + model_params + ) $$ LANGUAGE plpythonu VOLATILE PARALLEL UNSAFE;