Ejemplo n.º 1
0
 def test_separate_by_attribute(self):
     fxnGen = build_instance_generator(0.5)
     listInst = fxnGen(self.cInsts)
     for ixAttr in xrange(fxnGen.cAttrs):
         dictInst = dtree.separate_by_attribute(listInst, ixAttr)
         setValues = set([inst.listAttrs[ixAttr] for inst in listInst])
         self.assertEqual(len(setValues), len(dictInst))
         for cValue,listInstSeparate in dictInst.iteritems():
             for inst in listInstSeparate:
                 self.assertEqual(cValue, inst.listAttrs[ixAttr])
 def test_separate_by_attribute(self):
     fxnGen = build_instance_generator(0.5)
     listInst = fxnGen(self.cInsts)
     for ixAttr in xrange(fxnGen.cAttrs):
         dictInst = dtree.separate_by_attribute(listInst, ixAttr)
         setValues = set([inst.listAttrs[ixAttr] for inst in listInst])
         self.assertEqual(len(setValues), len(dictInst))
         for cValue, listInstSeparate in dictInst.iteritems():
             for inst in listInstSeparate:
                 self.assertEqual(cValue, inst.listAttrs[ixAttr])
 def test_compute_entropy_of_split(self):
     cAttrs = random.randint(2, 20)
     cValues = random.randint(1, 30)
     fxnGenOne = lambda _: build_entropy_one_instances(cAttrs, cValues)
     fxnGenOne.cAttrs = cAttrs
     fxnGenOne.cValues = cValues
     fxnGenZero = build_instance_generator(0.0, cAttrs=3)
     dblDelta = 0.01
     for fxnGen, dblP in zip((fxnGenOne, fxnGenZero, ), (1.0, 0.0)):
         listInst = fxnGen(self.cInsts)
         for ixAttr in xrange(fxnGen.cAttrs):
             dictInst = dtree.separate_by_attribute(listInst, ixAttr)
             dblEntropy = dtree.compute_entropy_of_split(dictInst)
             self.assertTrue(abs(dblEntropy - dblP) < dblDelta,
                             "%.3f not within %.3f of expected %.3f" %
                             (dblEntropy, dblDelta, dblP))
Ejemplo n.º 4
0
 def test_compute_entropy_of_split(self):
     cAttrs = random.randint(2,20)
     cValues = random.randint(1,30)
     fxnGenOne = lambda _: build_entropy_one_instances(cAttrs, cValues)
     fxnGenOne.cAttrs = cAttrs
     fxnGenOne.cValues = cValues
     fxnGenZero = build_instance_generator(0.0, cAttrs=3)
     dblDelta = 0.01
     for fxnGen,dblP in zip((fxnGenOne,fxnGenZero,),(1.0,0.0)):
         listInst = fxnGen(self.cInsts)
         for ixAttr in xrange(fxnGen.cAttrs):
             dictInst = dtree.separate_by_attribute(listInst, ixAttr)
             dblEntropy = dtree.compute_entropy_of_split(dictInst)
             self.assertTrue(abs(dblEntropy - dblP) < dblDelta,
                             "%.3f not within %.3f of expected %.3f" %
                             (dblEntropy, dblDelta, dblP))