474d15983f255906073e563932332c34eeb6e60d,tutorials/tpot_iris_pipeline.py,,,#,9

Before Change

// NOTE: Make sure that the class is labeled "class" in the data file
tpot_data = np.recfromcsv("PATH/TO/DATA/FILE", delimiter="COLUMN_SEPARATOR", dtype=np.float64)
features = np.delete(tpot_data.view(np.float64).reshape(tpot_data.size, -1), tpot_data.dtype.names.index("class"), axis=1)
training_features, testing_features, training_classes, testing_classes = \
    train_test_split(features, tpot_data["class"], random_state=None)

exported_pipeline = make_pipeline(

After Change

// NOTE: Make sure that the outcome column is labeled "target" in the data file
tpot_data = pd.read_csv("PATH/TO/DATA/FILE", sep="COLUMN_SEPARATOR", dtype=np.float64)
features = tpot_data.drop("target", axis=1)
training_features, testing_features, training_classes, testing_classes = \
            train_test_split(features, tpot_data["target"], random_state=None)

exported_pipeline = make_pipeline(

Instances