Using a rule-based classifier (2)

Description

This experiment investigates the performance of the rule-based classifier on the Zoo data set. The data set is split into a training and a test set, half of the examples are used to form a training set, and the rest are for testing. The classification accuracies on both the training and the test sets are determined for the rule-based classifier.

Input

Zoo [UCI MLR]

Output

Figure 6.3. The rule set of the rule-based classifier.

The rule set of the rule-based classifier.

Figure 6.4. The classification accuracy of the rule-based classifier on the training set.

The classification accuracy of the rule-based classifier on the training set.

Figure 6.5. The classification accuracy of the rule-based classifier on the test set.

The classification accuracy of the rule-based classifier on the test set.

Interpretation of the results

The second figure shows that the rule-based classifier perfectly classifies all training examples.

The third figure shows that the rule-based classifier perfectly classifies all but 6 of the 50 test examples.

Video

Workflow

rules_exp2.rmp

Keywords

rule-based classifier
supervised learning
classification

Operators

Apply Model
Map
Performance (Classification)
Read AML
Rule Induction
Split Data
Subprocess