Fit for AutoSklearn2Classifier fails whens input matrix is in CSR sparse Format #1204
Description
Describe the bug
When fitting a CSR matrix on the AutoSklearn2Classifier, the method fails and returns Trying to set illegal value 'gradient_boosting'
python version: 3.9
auto-sklearn version: 0.13.0
To Reproduce
Steps to reproduce the behavior:
import sklearn.datasets
from scipy import sparse
from autosklearn.experimental.askl2 import AutoSklearn2Classifier
X, y = sklearn.datasets.load_breast_cancer(return_X_y=True)
X_train, X_test, y_train, y_test = \
sklearn.model_selection.train_test_split(X, y, random_state=1)
X_train = sparse.csr_matrix(X_train)
automl = AutoSklearn2Classifier(
time_left_for_this_task=120,
per_run_time_limit=30
)
automl.fit(X_train, y_train, dataset_name='breast_cancer')
Note, the above works fine when using autosklearn.classification.AutoSklearnClassifier.
The use case for a CSR matrix is fitting text classification models after the text has been transformed into a TF-IDF format.