From dec6b5ab7b7cbb8bc8ee05f17063327a75331b6d Mon Sep 17 00:00:00 2001 From: PGijsbers Date: Tue, 17 Sep 2019 15:33:00 +0200 Subject: [PATCH] :white_check_mark: Update examples. --- examples/arff_example.py | 2 +- examples/classification_example.py | 2 +- examples/regression_example.py | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/examples/arff_example.py b/examples/arff_example.py index c484388b..943c17f4 100644 --- a/examples/arff_example.py +++ b/examples/arff_example.py @@ -4,7 +4,7 @@ print("Make sure you adjust the file path if not executed from the examples directory.") file_path = "../tests/data/breast_cancer_{}.arff" - automl = GamaClassifier(max_total_time=180, keep_analysis_log=False, n_jobs=1) + automl = GamaClassifier(max_total_time=180, keep_analysis_log=None, n_jobs=1) print("Starting `fit` which will take roughly 3 minutes.") automl.fit_arff(file_path.format('train')) diff --git a/examples/classification_example.py b/examples/classification_example.py index 26d7af7d..5846ec10 100644 --- a/examples/classification_example.py +++ b/examples/classification_example.py @@ -7,7 +7,7 @@ X, y = load_breast_cancer(return_X_y=True) X_train, X_test, y_train, y_test = train_test_split(X, y, stratify=y, random_state=0) - automl = GamaClassifier(max_total_time=180, keep_analysis_log=False, n_jobs=1) + automl = GamaClassifier(max_total_time=180, keep_analysis_log=None, n_jobs=1) print("Starting `fit` which will take roughly 3 minutes.") automl.fit(X_train, y_train) diff --git a/examples/regression_example.py b/examples/regression_example.py index ce24d76f..8f5432d7 100644 --- a/examples/regression_example.py +++ b/examples/regression_example.py @@ -7,7 +7,7 @@ X, y = load_boston(return_X_y=True) X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0) - automl = GamaRegressor(max_total_time=180, keep_analysis_log=False, n_jobs=1) + automl = GamaRegressor(max_total_time=180, keep_analysis_log=None, n_jobs=1) print("Starting `fit` which will take roughly 3 minutes.") automl.fit(X_train, y_train)