Pinv2Regressor

pinv2regressor.py

class Pinv2Regressor:
    def __init__(self, estimators, cv=5):
        self.estimators = estimators
        self.cv = cv

    def fit(self, X, y, verbose=False):
        preds = {}
        for k, estimator in self.estimators.items():
            if verbose:
                print(k, estimator)
            preds[k] = cross_val_predict(estimator, X, y, cv=self.cv)
            estimator.fit(X, y)
        preds = np.vstack(preds.values()).T
        self._weights = np.dot(pinv2(preds), y)
        return self

    def predict(self, X):
        preds = {}
        for k, estimator in self.estimators.items():
            preds[k] = estimator.predict(X)
        preds = np.vstack(preds.values()).T
        return np.dot(preds, self._weights)