co_forest.py 文件源码

def build_classifier(labeled, unlabeled):
        err = np.zeros(self.num_classifiers)
        err_prime = np.zeros(self.num_classifiers)
        s_prime = np.zeros(self.num_classifiers)

        inbags = [None] * self.num_classifiers

        np.random.seed(self.m_seed)

        num_original_labeled_insts = labeled.shape[0]

        # set up the random tree options
        self.num_kvalue = self.num_features
        if self.num_kvalue < 1:
            self.num_kvalue = int(np.log2(labeled.shape[1])) + 1
        self.estimator = self.estimator.set_params(**{"max_features": self.m_kvalue})

        pass