Python TreeLearner Examples

Example #1

    def test_report_widgets_regression(self):
        rep = OWReport.get_instance()
        data = Table("housing")
        widgets = self.regr_widgets

        w = self.create_widget(OWTreeGraph)
        mod = RegressionTreeLearner(max_depth=3)(data)
        mod.instances = data
        w.ctree(mod)
        w.create_report_html()
        rep.make_report(w)

        self._create_report(widgets, rep, data)

Example #2

    def test_report_widgets_regression(self):
        rep = OWReport.get_instance()
        data = Table("housing")
        widgets = self.regr_widgets

        w = self.create_widget(OWTreeGraph)
        mod = RegressionTreeLearner(max_depth=3)(data)
        mod.instances = data
        w.ctree(mod)
        w.create_report_html()
        rep.make_report(w)

        self._create_report(widgets, rep, data)

Example #3

File: owtreeviewer.py Project: waqarini/orange3

def test():
    """Standalone test"""
    import sys
    from PyQt4.QtGui import QApplication
    #    from Orange.classification.tree import TreeLearner
    from Orange.regression.tree import TreeLearner
    a = QApplication(sys.argv)
    ow = OWTreeGraph()
    # data = Table("iris")
    data = Table("housing")
    clf = TreeLearner()(data)
    clf.instances = data

    ow.ctree(clf)
    ow.show()
    ow.raise_()
    a.exec_()
    ow.saveSettings()

Example #4

File: owtreeviewer.py Project: RachitKansal/orange3

def test():
    """Standalone test"""
    import sys
    from AnyQt.QtWidgets import QApplication
#    from Orange.classification.tree import TreeLearner
    from Orange.regression.tree import TreeLearner
    a = QApplication(sys.argv)
    ow = OWTreeGraph()
    # data = Table("iris")
    data = Table("housing")
    clf = TreeLearner()(data)
    clf.instances = data

    ow.ctree(clf)
    ow.show()
    ow.raise_()
    a.exec_()
    ow.saveSettings()