SklearnClassifier.py 文件源码

def predict_log_proba(self,X):
        assert self.class_column > -1

        X1 = None
        if isinstance(X, pyisc.DataObject):
            assert X.class_column == self.class_column
            X1 = X.as_2d_array()
        elif isinstance(X, ndarray):
            X1 = X.copy()


        if X1 is not None:

            logps = self.compute_logp(X1)

            LogPs = [x-logsumexp(x) for x in array(logps).T] #normalized

            return array(LogPs)
        else:
            raise ValueError("Unknown type of data to score:", type(X))