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"""Winsorizes (truncates) univariate outliers outside of two standard deviations from the mean.""" | |
from h2oaicore.transformer_utils import CustomTransformer | |
import datatable as dt | |
import numpy as np | |
class MyTwoSigmaWinsorizer(CustomTransformer): | |
_testing_can_skip_failure = False # ensure tested as if shouldn't fail | |
@staticmethod | |
def get_default_properties(): | |
return dict(col_type="numeric", min_cols=1, max_cols=1, relative_importance=1) | |
def fit_transform(self, X: dt.Frame, y: np.array = None): | |
self.mean = X.mean1() | |
self.sd = X.sd1() | |
return self.transform(X) | |
def transform(self, X: dt.Frame): | |
X = dt.Frame(X) | |
if self.sd is not None and self.mean is not None: | |
X[self.mean - 2 * self.sd > dt.f[0], float] = self.mean - 2 * self.sd | |
X[self.mean + 2 * self.sd < dt.f[0], float] = self.mean + 2 * self.sd | |
return X |