-
Notifications
You must be signed in to change notification settings - Fork 49
Expand file tree
/
Copy pathNaiveBayesClassificationExample.java
More file actions
49 lines (40 loc) · 1.93 KB
/
NaiveBayesClassificationExample.java
File metadata and controls
49 lines (40 loc) · 1.93 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
package jdmp;/*
* Copyright (C) 2008-2015 by Holger Arndt
*
* This file is part of the Java Data Mining Package (JDMP).
* See the NOTICE file distributed with this work for additional
* information regarding copyright ownership and licensing.
*
* JDMP is free software; you can redistribute it and/or modify
* it under the terms of the GNU Lesser General Public License as
* published by the Free Software Foundation; either version 2
* of the License, or (at your option) any later version.
*
* JDMP is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU Lesser General Public License for more details.
*
* You should have received a copy of the GNU Lesser General Public
* License along with JDMP; if not, write to the
* Free Software Foundation, Inc., 51 Franklin St, Fifth Floor,
* Boston, MA 02110-1301 USA
*/
import org.jdmp.core.algorithm.classification.bayes.NaiveBayesClassifier;
import org.jdmp.core.dataset.DataSet;
import org.jdmp.core.dataset.ListDataSet;
public class NaiveBayesClassificationExample {
public static void main(String[] args) {
// load example data set
ListDataSet dataSet = DataSet.Factory.IRIS();
// create a classifier
NaiveBayesClassifier classifier = new NaiveBayesClassifier();
// train the classifier using all data
classifier.trainAll(dataSet);
// use the classifier to make predictions
classifier.predictAll(dataSet);
// get the results
double accurary = dataSet.getAccuracy();
System.out.println("accuracy: " + accurary);
}
}