classifiers.py 文件源码

def build(self, A, categories, K=None):
        '''Builds the classifier give the data points in A and the categories'''

        # figure out how many categories there are and get the mapping (np.unique)
        unique, mapping = np.unique(np.array(categories.T), return_inverse=True)
        self.num_classes = len(unique)
        self.num_features = A.shape[0]
        self.categories = categories

        # for each category i, build the set of exemplars
        for i in range(self.num_classes):
            if K is None:
                self.exemplars.append(A[(mapping == i),:])
            else:
                codebook,codes = vq.kmeans(A[(mapping == i),:],K)
                self.exemplars.append(codebook)

        return