def lrLearner(data, protectedIndex, protectedValue):
h = lr.lrSKL(data)
return randomOneSideRelabelData(h, data, protectedIndex, protectedValue)
def svmLinearLearner(data, protectedIndex, protectedValue):
h = svm.svmSKL(data, kernel='linear', verbose=True)
return randomOneSideRelabelData(h, data, protectedIndex, protectedValue)
def boostingLearner(data, protectedIndex, protectedValue):
h = boosting.boost(data)
return randomOneSideRelabelData(h, data, protectedIndex, protectedValue)
def lrLearner(data, protectedIndex, protectedValue): h = lr.lrSKL(data) return randomOneSideRelabelData(h, data, protectedIndex, protectedValue)
def svmLinearLearner(data, protectedIndex, protectedValue): h = svm.svmSKL(data, kernel='linear', verbose=True) return randomOneSideRelabelData(h, data, protectedIndex, protectedValue)
def boostingLearner(data, protectedIndex, protectedValue): h = boosting.boost(data) return randomOneSideRelabelData(h, data, protectedIndex, protectedValue)