Fixed catboost and added new tqdm

src/arfs/feature_selection/allrelevant.py

@@ -56,7 +56,7 @@
 import scipy as sp
 
 from typing import Tuple
-from tqdm import tqdm
+from tqdm.auto import tqdm
 from sklearn.utils import check_random_state, check_X_y
 from sklearn.base import BaseEstimator, is_regressor, is_classifier, clone
 
@@ -494,7 +494,7 @@ def _get_tree_num(self, n_feat):
         n_estimators : int
             the number of trees
         """
-        depth = self.estimator.get_params()["max_depth"]
+        depth = self.estimator.get_params()["max_depth"] if not self.is_cat else self.estimator.get_param("max_depth")
         if depth is None:
             depth = 10
         # how many times a feature should be considered on average

src/arfs/feature_selection/mrmr.py

@@ -12,7 +12,7 @@
 import pandas as pd
 from sklearn.base import BaseEstimator
 from sklearn.utils.validation import check_is_fitted
-from tqdm import tqdm
+from tqdm.auto import tqdm
 from sklearn.feature_selection._base import SelectorMixin
 from ..association import (
     f_stat_classification_parallel,

src/arfs/preprocessing.py

@@ -11,7 +11,7 @@
 
 # Settings and libraries
 from __future__ import print_function
-from tqdm import tqdm
+from tqdm.auto import tqdm
 
 # pandas
 import pandas as pd