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)