@@ -49,7 +49,7 @@ class UnconditionalDistfitRegressor(BaseProbaRegressor):
4949 }
5050
5151 def __init__ (
52- self , distr_type = "norm" , random_state = None , fit_kde = True , fit_histogram = False
52+ self , distr_type = "norm" , random_state = None , fit_histogram = False
5353 ):
5454 """
5555 Initialize UnconditionalDistfitRegressor.
@@ -61,14 +61,11 @@ def __init__(
6161 distfit docs for full list).
6262 random_state : int or None
6363 Random seed for reproducibility.
64- fit_kde : bool, default=True
65- If True, fit a KDE (kernel density estimate) using distfit's kde option.
6664 fit_histogram : bool, default=False
6765 If True, fit a histogram using distfit's histogram option.
6866 """
6967 self .distr_type = distr_type
7068 self .random_state = random_state
71- self .fit_kde = fit_kde
7269 self .fit_histogram = fit_histogram
7370 super ().__init__ ()
7471
@@ -77,11 +74,11 @@ def _fit(self, X, y, C=None):
7774 from distfit import distfit
7875
7976 y_arr = y .values .flatten () if hasattr (y , "values" ) else np .asarray (y ).flatten ()
80- # Block KDE usage due to scipy.stats.kde deprecation in distfit
81- if self .fit_kde or self . distr_type == "kde" :
77+ # KDE support removed due to scipy.stats.kde deprecation in distfit
78+ if self .distr_type == "kde" :
8279 raise RuntimeError (
83- "distfit KDE support broken due to scipy.stats.kde removal . "
84- "Please use a different distribution type or set fit_kde=False ."
80+ "KDE support is removed due to scipy.stats.kde deprecation in distfit . "
81+ "Please use a different distribution type."
8582 )
8683 if self .fit_histogram :
8784 self .distfit_ = distfit (distr = "histogram" , random_state = self .random_state )
@@ -100,8 +97,8 @@ def _predict_proba(self, X):
10097 def get_test_params (cls , parameter_set = "default" ):
10198 """Return testing parameter sets for automated tests."""
10299 return [
103- {"distr_type" : "norm" , "fit_kde" : False , " fit_histogram" : False },
104- {"distr_type" : "laplace" , "fit_kde" : True , " fit_histogram" : False },
100+ {"distr_type" : "norm" , "fit_histogram" : False },
101+ {"distr_type" : "laplace" , "fit_histogram" : False },
105102 ]
106103
107104
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