Я запускаю это:
# Hyperparameter tuning - Random Forest #
# Hyperparameters' grid
parameters = {'n_estimators': list(range(100, 250, 25)), 'criterion': ['gini', 'entropy'],
'max_depth': list(range(2, 11, 2)), 'max_features': [0.1, 0.2, 0.3, 0.4, 0.5],
'class_weight': [{0: 1, 1: i} for i in np.arange(1, 4, 0.2).tolist()], 'min_samples_split': list(range(2, 7))}
# Instantiate random forest
from sklearn.ensemble import RandomForestClassifier
classifier = RandomForestClassifier(random_state=0)
# Execute grid search and retrieve the best classifier
from sklearn.model_selection import GridSearchCV
classifiers_grid = GridSearchCV(estimator=classifier, param_grid=parameters, scoring='balanced_accuracy',
cv=5, refit=True, n_jobs=-1)
classifiers_grid.fit(X, y)
и получаю это предупреждение:
.../anaconda/lib/python3.7/site-packages/sklearn/model_selection/_validation.py:536: FitFailedWarning: Estimator fit failed. The score on this train-test partition for these parameters will be set to nan. Details:
TypeError: '<' not supported between instances of 'str' and 'int'
Почему это и как я могу это исправить?