kmeans.py 文件源码

def __init__(self, n_clusters, max_iter=5, metric='euclidean', tolerance=1e-5, init_strategy='kmeans++',
                 batch_size=0.2, oom_strategy='memmap', fixed_seed=False, stride=None, n_jobs=None, skip=0):

        if stride is not None:
            raise ValueError("stride is a dummy value in MiniBatch Kmeans")
        if batch_size > 1:
            raise ValueError("batch_size should be less or equal to 1, but was %s" % batch_size)

        self._cluster_centers_iter = None
        self._centers_iter_list = []

        super(MiniBatchKmeansClustering, self).__init__(n_clusters, max_iter, metric,
                                                        tolerance, init_strategy, False,
                                                        oom_strategy, stride=stride, n_jobs=n_jobs, skip=skip)

        self.set_params(batch_size=batch_size)