def testDummySet1(setFunc=setEntropy, infoFunc=infoGain):
"""Correct classification rate is 1.0"""
examples, attrValues, labelName, labelValues = getDummyDataset1()
print 'Testing dummy dataset 1. Number of examples %d.' % len(examples)
tree = makeTree(examples, attrValues, labelName, setFunc, infoFunc)
print 'Tree is as follows:\n%s\n' % str(tree)
print 'Tree size: %d.\n' % tree.count()
examples, attrValues, labelName, labelValues = getDummyDataset1(test=True)
evaluation = evaluateTree(tree, examples, labelName)
print 'Results for training set:\n%s\n' % str(evaluation)
printDemarcation()
return (tree, evaluation)
def testDummySet1(setFunc = setEntropy, infoFunc = infoGain):
"""Correct classification rate is 1.0"""
examples,attrValues,labelName,labelValues = getDummyDataset1()
print 'Testing dummy dataset 1. Number of examples %d.'%len(examples)
tree = makeTree(examples, attrValues, labelName, setFunc, infoFunc)
print 'Tree is as follows:\n%s\n'%str(tree)
print 'Tree size: %d.\n'%tree.count()
examples,attrValues,labelName,labelValues = getDummyDataset1(test=True)
evaluation = evaluateTree(tree,examples,labelName)
print 'Results for training set:\n%s\n'%str(evaluation)
printDemarcation()
return (tree,evaluation)
