Example
# imports
import weka.core.converters.ConverterUtils.DataSource as DS
import weka.classifiers.Evaluation as Evaluation
import weka.classifiers.trees.J48 as J48
import java.util.Random as Random
import os
# load data
data = DS.read(os.environ.get("MOOC_DATA") + os.sep + "anneal.arff")
data.setClassIndex(data.numAttributes() - 1)
# configure classifier
cls = J48()
cls.setOptions(["-C", "0.3"])
# cross-validate classifier
evl = Evaluation(data)
evl.crossValidateModel(cls, data, 10, Random(1))
# print statistics
print(evl.toSummaryString("=== J48 on anneal (stats) ===", False))
print(evl.toMatrixString("=== J48 on anneal (confusion matrix) ==="))
