Classifier - Software Development Case Studies in Java - page 80

Table 4.2 Training set

Item AC ABS Expected category

1 Yes Yes High

2 No No Low

3 Yes No Medium

4 No Yes Medium

create the items, by means of the createItem() method, and add them to
the training set mapping them to their categories;

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create a decision tree classifier based on the training set; and

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check if the classifier classifies correctly the test set element.

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public class TestTraining extends TestCase {
public TestTraining(String arg0) {
super (arg0);

}
private Item createItem(String ac, String abs){
Feature[] features # new Feature[] {
new Feature("AC",ac,yn),
new Feature("ABS",abs,yn)

};
return new Item("car",features);

}
private FeatureType yn # new FeatureType("YesNo",
new String[]{"yes","no"});

public void testExample(){
Map items # new HashMap();
Map features # new HashMap();
features.put("AC",yn);
features.put("ABS",yn);
Item item1 # createItem("yes","yes");
items.put(item1,"high");
Item item2 # createItem("yes","no");
items.put(item2,"medium");
Item item3 # createItem("no","yes");
items.put(item3,"medium");
Item item4 # createItem("no","no");
items.put(item4,"low");
DecisionTree dc # new DecisionTree(items,features);
assertEquals("high",dc.assignCategory(item1));
assertEquals("medium",dc.assignCategory(item2));
assertEquals("medium",dc.assignCategory(item3));
assertEquals("low",dc.assignCategory(item4));

}

}