def _test_basic_flow_sv_2dfs(self, cv, is_cl):
df_training = utils.get_input_df(100)
df_validation = utils.get_input_df(100)
df_test = utils.get_input_df(10)
target_column = "target_cl" if is_cl else "target_rg"
feature_columns = ["column{}".format(i) for i in range(6)]
model = cv.fit_sv_pandas(df_training, target_column, feature_columns,
df_validation)
self._assert_prediction(model, df_test, is_cl)
def execute_scenario(model_type, is_cl, with_prep, cv_type, holdout_type):
cv = _get_cv(model_type, is_cl, with_prep, cv_type)
df_training = utils.get_input_df(100, with_prep)
df_validation = utils.get_input_df(100, with_prep)
df_test = utils.get_input_df(10, with_prep)
target_column = "target_cl" if is_cl else "target_rg"
feature_columns = ["column{}".format(i) for i in range(6)]
model = cv.fit_cv_pandas(df_training, target_column, feature_columns, n_fold=3) \
if holdout_type == "cv" \
else cv.fit_holdout_pandas(df_training, target_column, feature_columns, ratio_training=0.8) \
if holdout_type == "holdout_ratio" \
else cv.fit_holdout_pandas(df_training, target_column, feature_columns, df_validation)
_assert_prediction(model, df_test, is_cl)