Increasing max_iter to 1000 for LogisticRegression used in PrejudiceR…

…emover (#254)
Trusted-AI · Sep 2, 2022 · c0bd309 · c0bd309
1 parent efc6f9a
commit c0bd309
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diff --git a/aif360/algorithms/inprocessing/kamfadm-2012ecmlpkdd/fadm/lr/pr.py b/aif360/algorithms/inprocessing/kamfadm-2012ecmlpkdd/fadm/lr/pr.py
@@ -236,7 +236,7 @@ def init_coef(self, itype, X, y, s):
             coef = self.coef_.reshape(self.n_sfv_, self.n_features_)
 
             for i in range(self.n_sfv_):
-                clr = LogisticRegression(C=self.C, penalty='l2',
+                clr = LogisticRegression(C=self.C, penalty='l2', max_iter=1000,
                                          fit_intercept=False)
                 clr.fit(X[s == i, :], y[s == i])
                 coef[i, :] = clr.coef_

diff --git a/aif360/algorithms/inprocessing/prejudice_remover.py b/aif360/algorithms/inprocessing/prejudice_remover.py
@@ -27,6 +27,7 @@
         - kamfadm-2012ecmlpkdd/train_nb.py
     * fixed typo in kamfadm-2012ecmlpkdd/fadm/lr/pr.py:244 (typeError -> TypeError)
     * removed commands.py and instead use subprocess.getoutput
+    * increased max_iter to 1000 in kamfadm-2012ecmlpkdd/fadm/lr/pr.py:239
 
 Notes from fairness-comparison's KamishimaAlgorithm.py on changes made to
 original Kamishima code.