def task(self): listInst = dtree.load_csv_dataset(datadir("data.csv")) br = dtree.boost(listInst) return {"chart": {"defaultSeriesType": "line"}, "title": {"text": "Boosting Classifier Weights"}, "xAxis": {"title": {"text": "Classifier Number"}}, "series": [{"name": "Classifier Weights", "data": br.listDblCferWeight}]}
def test_boost(self): listAttr = randlist(0, 5, 10) listInst = [dtree.Instance(listAttr, True) for _ in xrange(100)] listInstFalse = random.sample(listInst, 10) for inst in listInstFalse: inst.fLabel = False listInstCopy = [inst.copy() for inst in listInst] br = dtree.boost(listInstCopy) dblWeightExpected = dtree.classifier_weight(0.1) self.assertAlmostEqual(br.listDblCferWeight[0], dblWeightExpected)
def test_boost(self): listAttr = randlist(0,5,10) listInst = [dtree.Instance(listAttr, True) for _ in xrange(100)] listInstFalse = random.sample(listInst,10) for inst in listInstFalse: inst.fLabel = False listInstCopy = [inst.copy() for inst in listInst] br = dtree.boost(listInstCopy) dblWeightExpected = dtree.classifier_weight(0.1) self.assertAlmostEqual(br.listDblCferWeight[0], dblWeightExpected)
def task(self): listInst = dtree.load_csv_dataset(datadir("data.csv")) br = dtree.boost(listInst) return { "chart": { "defaultSeriesType": "line" }, "title": { "text": "Boosting Classifier Weights" }, "xAxis": { "title": { "text": "Classifier Number" } }, "series": [{ "name": "Classifier Weights", "data": br.listDblCferWeight }] }
def test_boost_maxrounds(self): cRound = random.randint(2, 25) listInst = build_consistent_generator()(100) br = dtree.boost(listInst, cMaxRounds=cRound) self.assertTrue(len(br.listCfer) <= cRound) self.assertTrue(len(br.listDblCferWeight) <= cRound)
def test_boost_maxrounds(self): cRound = random.randint(2,25) listInst = build_consistent_generator()(100) br = dtree.boost(listInst, cMaxRounds=cRound) self.assertTrue(len(br.listCfer) <= cRound) self.assertTrue(len(br.listDblCferWeight) <= cRound)
def dt_build_model(listInst, cRounds): """Build boosted committee from instances""" return dtree.boost(listInst, cRounds)