Ada Boost: Remove option 'algorithm' from the widget

Orange/widgets/model/owadaboost.py

@@ -1,4 +1,5 @@
 from AnyQt.QtCore import Qt
+from AnyQt.QtWidgets import QFormLayout, QLabel
 
 from Orange.base import Learner
 from Orange.data import Table
@@ -27,14 +28,11 @@ class OWAdaBoost(OWBaseLearner):
     class Inputs(OWBaseLearner.Inputs):
         learner = Input("Learner", Learner)
 
-    #: Algorithms for classification problems
-    algorithms = ["SAMME", "SAMME.R"]
     #: Losses for regression problems
     losses = ["Linear", "Square", "Exponential"]
 
     n_estimators = Setting(50)
     learning_rate = Setting(1.)
-    algorithm_index = Setting(1)
     loss_index = Setting(0)
     use_random_seed = Setting(False)
     random_seed = Setting(0)
@@ -46,36 +44,36 @@ class Error(OWBaseLearner.Error):
 
     def add_main_layout(self):
         # this is part of init, pylint: disable=attribute-defined-outside-init
-        box = gui.widgetBox(self.controlArea, "Parameters")
+        grid = QFormLayout()
+        box = gui.widgetBox(self.controlArea, box=True, orientation=grid)
         self.base_estimator = self.DEFAULT_BASE_ESTIMATOR
-        self.base_label = gui.label(
-            box, self, "Base estimator: " + self.base_estimator.name.title())
+        self.base_label = QLabel(self.base_estimator.name.title())
+        grid.addRow("Base estimator:", self.base_label)
 
         self.n_estimators_spin = gui.spin(
-            box, self, "n_estimators", 1, 10000, label="Number of estimators:",
-            alignment=Qt.AlignRight, controlWidth=80,
+            None, self, "n_estimators", 1, 10000,
+            controlWidth=80, alignment=Qt.AlignRight,
             callback=self.settings_changed)
+        grid.addRow("Number of estimators:", self.n_estimators_spin)
+
         self.learning_rate_spin = gui.doubleSpin(
-            box, self, "learning_rate", 1e-5, 1.0, 1e-5,
-            label="Learning rate:", decimals=5, alignment=Qt.AlignRight,
-            controlWidth=80, callback=self.settings_changed)
+            None, self, "learning_rate", 1e-5, 1.0, 1e-5, decimals=5,
+            alignment=Qt.AlignRight,
+            callback=self.settings_changed)
+        grid.addRow("Learning rate:", self.learning_rate_spin)
+
+        self.reg_algorithm_combo = gui.comboBox(
+            None, self, "loss_index", items=self.losses,
+            callback=self.settings_changed)
+        grid.addRow("Loss (regression):", self.reg_algorithm_combo)
+
+        box = gui.widgetBox(self.controlArea, box="Reproducibility")
         self.random_seed_spin = gui.spin(
             box, self, "random_seed", 0, 2 ** 31 - 1, controlWidth=80,
             label="Fixed seed for random generator:", alignment=Qt.AlignRight,
             callback=self.settings_changed, checked="use_random_seed",
             checkCallback=self.settings_changed)
 
-        # Algorithms
-        box = gui.widgetBox(self.controlArea, "Boosting method")
-        self.cls_algorithm_combo = gui.comboBox(
-            box, self, "algorithm_index", label="Classification algorithm:",
-            items=self.algorithms,
-            orientation=Qt.Horizontal, callback=self.settings_changed)
-        self.reg_algorithm_combo = gui.comboBox(
-            box, self, "loss_index", label="Regression loss function:",
-            items=self.losses,
-            orientation=Qt.Horizontal, callback=self.settings_changed)
-
     def create_learner(self):
         if self.base_estimator is None:
             return None
@@ -85,7 +83,6 @@ def create_learner(self):
             learning_rate=self.learning_rate,
             random_state=self.random_seed,
             preprocessors=self.preprocessors,
-            algorithm=self.algorithms[self.algorithm_index],
             loss=self.losses[self.loss_index].lower())
 
     @Inputs.learner
@@ -97,18 +94,15 @@ def set_base_learner(self, learner):
             # Clear the error and reset to default base learner
             self.Error.no_weight_support()
             self.base_estimator = None
-            self.base_label.setText("Base estimator: INVALID")
+            self.base_label.setText("INVALID")
         else:
             self.base_estimator = learner or self.DEFAULT_BASE_ESTIMATOR
-            self.base_label.setText(
-                "Base estimator: %s" % self.base_estimator.name.title())
+            self.base_label.setText(self.base_estimator.name.title())
         self.learner = self.model = None
 
     def get_learner_parameters(self):
         return (("Base estimator", self.base_estimator),
                 ("Number of estimators", self.n_estimators),
-                ("Algorithm (classification)", self.algorithms[
-                    self.algorithm_index].capitalize()),
                 ("Loss (regression)", self.losses[
                     self.loss_index].capitalize()))
 

Orange/widgets/model/tests/test_owadaboost.py

@@ -14,9 +14,6 @@ def setUp(self):
             OWAdaBoost, stored_settings={"auto_apply": False})
         self.init()
         self.parameters = [
-            ParameterMapping('algorithm', self.widget.cls_algorithm_combo,
-                             self.widget.algorithms,
-                             problem_type="classification"),
             ParameterMapping('loss', self.widget.reg_algorithm_combo,
                              [x.lower() for x in self.widget.losses],
                              problem_type="regression"),

i18n/si/msgs.jaml

@@ -2017,7 +2017,6 @@ ensembles/ada_boost.py:
         '`base_estimator` is deprecated (to be removed in 3.39): use `estimator` instead.': false
     class `SklAdaBoostClassificationLearner`:
         def `__init__`:
-            SAMME.R: false
             deprecated: false
     class `SklAdaBoostRegressionLearner`:
         def `__init__`:
@@ -9510,35 +9509,28 @@ widgets/model/owadaboost.py:
         adaboost, boost: adaboost, boost
         class `Inputs`:
             Learner: Učni algoritem
-        SAMME: true
-        SAMME.R: true
         Linear: Linearna
         Square: Kvadratna
         Exponential: Eksponentna
         class `Error`:
             The base learner does not support weights.: Učni algoritem ne podpira uteži.
         def `add_main_layout`:
-            Parameters: Parametri
-            'Base estimator: ': 'Osnovni model: '
+            Base estimator:: Osnovni model:
             n_estimators: false
             Number of estimators:: Število modelov:
             learning_rate: false
             Learning rate:: Hitrost učenja:
+            loss_index: false
+            Loss (regression):: Funkcija izgube (za regresijo)
+            Reproducibility: Ponovljivost
             random_seed: false
             Fixed seed for random generator:: Seme generatorja naključnih števil:
             use_random_seed: false
-            Boosting method: Metoda pospeševanja (boosting)
-            algorithm_index: false
-            Classification algorithm:: Algoritem (za klasifikacijo):
-            loss_index: false
-            Regression loss function:: Funkcija izgube (za regresijo):
         def `set_base_learner`:
-            'Base estimator: INVALID': Osnovni model: neveljaven
-            'Base estimator: %s': Osnovni model: %s
+            INVALID: NEVELJAVEN
         def `get_learner_parameters`:
             Base estimator: Osnovni model
             Number of estimators: Število modelov
-            Algorithm (classification): Algoritem (za klasifikacijo)
             Loss (regression): Izguba (za regresijo)
     __main__: false
     iris: false