imputation.py 文件源码

def get(self, X):
        X = np.array(X)
        X_nan = np.isnan(X)
        imputed = self.meanImput(X.copy())

        if len(self.estimators_) > 1:
            for i, estimator_ in enumerate(self.estimators_):
                X_s = np.delete(imputed, i, 1)
                y_nan = X_nan[:, i]

                X_unk = X_s[y_nan]

                result_ = []
                if len(X_unk) > 0:
                    for unk in X_unk:
                        result_.append(estimator_.predict(unk))
                    X[y_nan, i] = result_

        return X