def main(): import adaboost from numpy import mat, ones datMat, classLabels = adaboost.loadSimpleData() D = mat(ones((5, 1)) / 5) bestStump, minError, bestClasEst = adaboost.buildStump( datMat, classLabels, D) classifierArr, aggClassEst = adaboost.adaBoostTrainDS(datMat, classLabels, 9) adaboost.adaClassify([[5, 5], [0, 0]], classifierArr)
def test(): datMat, classLabels = adaboost.loadSimpleData() print("dataMat: [%s] classLabels: [%s]" % (datMat, classLabels)) #adaboost.plt(datMat, classLabels) D = mat(ones((5,1))/5) bestStump, minError, bestClassEst = adaboost.buildStump(datMat, classLabels, D) print("bestStump: ", bestStump, " minError:", minError, " bestClasEst:", bestClassEst) classifierArray, classifierEst = adaboost.adaBoostTrainDS(datMat, classLabels, 9) print("classifierArray:", classifierArray) print(adaboost.adaClassify([0,0], classifierArray)) print(adaboost.adaClassify([[5,5],[0,0]], classifierArray))
def test_load_simple_data(self): #print "test_load_simple_data" dataMat, classLabels = adaboost.loadSimpleData()
def test_ada_classify(self): print "test_ada_classify" dataMat, classLabels = adaboost.loadSimpleData() classifierArr = adaboost.adaBoostTrainDS(dataMat, classLabels, 9)
def test_adaboost_train_ds(self): #print "test_adaboost_train_ds" dataMat, classLabels = adaboost.loadSimpleData() classifierArray = adaboost.adaBoostTrainDS(dataMat, classLabels, 9)
def test_build_stump(self): #print "test_build_stump" dataMat, classLabels = adaboost.loadSimpleData() D = mat(ones((5, 1)) / 5) result = adaboost.buildStump(dataMat, classLabels, D)