Modified SGD widget, SGDClassifier and SGDRegressionLearner to comply…

… with sklearn 0.21 changes (tol and max_iter)
biolab · Feb 22, 2018 · 936cf1f · 936cf1f
1 parent 60c741f
commit 936cf1f
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Showing 3 changed files with 14 additions and 10 deletions.
diff --git a/Orange/classification/sgd.py b/Orange/classification/sgd.py
@@ -14,7 +14,7 @@ class SGDClassificationLearner(SklLearner):
     preprocessors = SklLearner.preprocessors + [Normalize()]
 
     def __init__(self, loss='hinge', penalty='l2', alpha=0.0001,
-                 l1_ratio=0.15,fit_intercept=True, max_iter=5,
+                 l1_ratio=0.15, fit_intercept=True, max_iter=5,
                  tol=None, shuffle=True, epsilon=0.1, random_state=None,
                  learning_rate='invscaling', eta0=0.01, power_t=0.25,
                  warm_start=False, average=False, preprocessors=None):

diff --git a/Orange/regression/linear.py b/Orange/regression/linear.py
@@ -84,8 +84,8 @@ class SGDRegressionLearner(LinearRegressionLearner):
     preprocessors = SklLearner.preprocessors + [Normalize()]
 
     def __init__(self, loss='squared_loss', penalty='l2', alpha=0.0001,
-                 l1_ratio=0.15, fit_intercept=True, n_iter=5, shuffle=True,
-                 epsilon=0.1, n_jobs=1, random_state=None,
+                 l1_ratio=0.15, fit_intercept=True, max_iter=5, tol=None,
+                 shuffle=True, epsilon=0.1, n_jobs=1, random_state=None,
                  learning_rate='invscaling', eta0=0.01, power_t=0.25,
                  class_weight=None, warm_start=False, average=False,
                  preprocessors=None):

diff --git a/Orange/widgets/model/owsgd.py b/Orange/widgets/model/owsgd.py
@@ -76,7 +76,8 @@ class Outputs(OWBaseLearner.Outputs):
     learning_rate_index = Setting(0)
     eta0 = Setting(.01)
     power_t = Setting(.25)
-    max_iter = Setting(5)
+    max_iter = Setting(1000)
+    tol = Setting(1e-3)
 
     def add_main_layout(self):
         self._add_algorithm_to_layout()
@@ -154,6 +155,13 @@ def _add_learning_params_to_layout(self):
             box, self, 'max_iter', 1, MAXINT - 1, label='Number of iterations: ',
             controlWidth=80, alignment=Qt.AlignRight,
             callback=self.settings_changed)
+
+        self.tol_spin = gui.spin(
+            box, self, 'tol', 0, 10., .1e-3, spinType=float, controlWidth=80,
+            label='Tolerance (stopping criterion): ', alignment=Qt.AlignRight,
+            callback=self.settings_changed)
+        gui.separator(box, height=12)
+
         # Wrap shuffle_cbx inside another hbox to align it with the random_seed
         # spin box on OSX
         self.shuffle_cbx = gui.checkBox(
@@ -247,6 +255,7 @@ def create_learner(self):
             eta0=self.eta0,
             power_t=self.power_t,
             max_iter=self.max_iter,
+            tol=self.tol,
             preprocessors=self.preprocessors,
             **params)
 
@@ -306,11 +315,6 @@ def update_model(self):
                 coeffs.name = "coefficients"
         self.Outputs.coefficients.send(coeffs)
 
-    @classmethod
-    def migrate_settings(cls, settings_, version):
-        if version < 2:
-            settings_["max_iter"] = settings_.pop("n_iter", 5)
-
 
 if __name__ == '__main__':
     import sys
@@ -324,4 +328,4 @@ def migrate_settings(cls, settings_, version):
     ow.set_data(d)
     ow.show()
     a.exec_()
-    ow.saveSettings()
+    ow.saveSettings()