source: orange/Orange/doc/widgets/Regression/RegressionTree.htm @ 9671:a7b056375472

Revision 9671:a7b056375472, 2.5 KB checked in by anze <anze.staric@…>, 2 years ago (diff)

Moved orange to Orange (part 2)

Line 
1<html>
2<head>
3<title>Regression Tree</title>
4<link rel=stylesheet href="../../../style.css" type="text/css" media=screen>
5<link rel=stylesheet href="../../../style-print.css" type="text/css" media=print></link>
6</head>
7
8<body>
9
10<h1>Regression Tree Learner</h1>
11
12<img class="screenshot" src="../icons/RegressionTree.png">
13<p>Regression Tree Learner</p>
14
15<h2>Channels</h2>
16
17<h3>Inputs</h3>
18
19<DL class=attributes>
20<DT>Examples (ExampleTable)</DT>
21<DD>A table with training examples</DD>
22</dl>
23
24<h3>Outputs</h3>
25<DL class=attributes>
26<DT>Learner</DT>
27<DD>The classification tree learning algorithm with settings as specified in the dialog.</DD>
28
29<DT>Regression Tree</DT>
30<DD>Trained classifier (a subtype of Classifier)</DD>
31</dl>
32
33<P>Signal <code>Regression Tree</code> sends data only if the learning data (signal <code>Examples</code> is present.</P>
34
35<h2>Description</h2>
36
37<p>This widget constructs a regression tree learning algorithm. As all widgets for classification and regression, this widget provides a learner and classifier/regressor on the output. Learner is a learning algorithm with settings as specified by the user. It can be fed into widgets for testing learners, for instance <code>Test Learners</code>.</p>
38
39<img class="leftscreenshot" src="RegressionTree.png" alt="Regression Tree Widget" border=0/>
40
41<P>Learner can be given a name under which it will appear in, say, <code>Test Learners</code>. The default name is "Regression Tree".</P>
42
43<P>If <code>Binarization</code> is checked, the values of multivalued attributes are split into two groups (based on the statistics in the particular node) to yield a binary tree. Binarization gets rid of the usual measures' bias towards attributes with more values and is generally recommended.</P>
44
45<P>The widget can be instructed to prune the tree during induction by setting <span class="option">Do not split nodes with less instances than</span>. For pruning after induction, there is pruning with m-estimate of error.</P>
46
47<P>After changing one or more settings, you need to push <span class="option">Apply</span>, which will put the new learner on the output and, if the training examples are given, construct a new classifier and output it as well.</P>
48
49<h2>Examples</h2>
50
51<P>There are two typical uses of this widget. First, you may want to induce the model and check what it looks like with the schema below.
52
53<img class="screenshot" src="RegressionTree-Schema.png">
54
55<P>The second schema checks the accuracy of the algorithm.</P>
56
57<img class="screenshot" src="RegressionTree-Schema2.png">
58
59</body>
60</html>
Note: See TracBrowser for help on using the repository browser.