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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def decision_function(self, X):
 """ Generate an inlier score for each test data example. Parameters X : array Test data, of dimension N times d (rows are examples, columns are data dimensions) Returns: ------- scores : array A vector of length N, where each element contains an inlier score in the range 0-1 (outliers have values close to zero, inliers have values close to one). """

        predictions = self.predict_proba(X)
        out = np.zeros((predictions.shape[0], 1))
        out[:, 0] = 1 - predictions[:, -1]
        return out