DecisionTreeExample.java

package com.github.lwhite1.tablesaw.api.ml.classification;

import com.github.lwhite1.tablesaw.api.Table;
import com.github.lwhite1.tablesaw.api.plot.Scatter;
import com.github.lwhite1.tablesaw.util.Example;

/**
 *
 */
public class DecisionTreeExample extends Example {

    public static void main(String[] args) throws Exception {

        Table example = Table.createFromCsv("data/KNN_Example_1.csv");
        out(example.structure().printHtml());

        // show all the label values
        out(example.shortColumn("Label").asSet());

        Scatter.show("Example data", example.nCol(0), example.nCol(1), example.splitOn(example.shortColumn(2)));

        // two fold validation
        Table[] splits = example.sampleSplit(.5);
        Table train = splits[0];
        Table test = splits[1];

        DecisionTree model = DecisionTree.learn(10, train.shortColumn(2), train.nCol("X"), train.nCol("Y"));

        ConfusionMatrix matrix = model.predictMatrix(test.shortColumn(2), test.nCol("X"), test.nCol("Y"));

        // Prediction
        out(matrix.toTable().printHtml());
        out(String.valueOf(matrix.accuracy()));
    }
}