def __init__(self, dataset, feature_selector, mu=None, sigma=None, parent_preprocess=None):
        super().__init__(parent_preprocess)
        self.feature_selector = feature_selector
        self.mu = self._get_values(dataset)[self.feature_selector].mean() if mu is None else mu
        self.sigma = self._get_values(dataset)[self.feature_selector].std() if sigma is None else sigma
Transform given features to their Z-score
dataset/ETHPy150Open SMART-Lab/smartlearner/smartlearner/preprocessors.py/NormalizeFeature.__init__