X, y = load_digits(return_X_y=True)
X_train, X_test, y_train, y_test = train_test_split(
X, y, stratify=y, random_state=0
)
# Add checks on individuals (reproducibility)
gama.fit(X_train, y_train)
GAMA infers some features as categoricals (which is expected behavior, though incorrect).
This in turn creates new feature names, now some are int and some are str, e.g.: ['1_1', '1_2', 2, 3, ...]
This results in an error during evaluation: <class 'TypeError'> Feature names are only supported if all input features have string name.
Postponing on fixing this until #169 is merged.
For people encountering issues with this behavior, please use pandas dataframes for now.
GAMA infers some features as categoricals (which is expected behavior, though incorrect). This in turn creates new feature names, now some are
intand some arestr, e.g.:['1_1', '1_2', 2, 3, ...]This results in an error during evaluation:<class 'TypeError'> Feature names are only supported if all input features have string name.Postponing on fixing this until #169 is merged.
For people encountering issues with this behavior, please use pandas dataframes for now.