RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning Publication Song, H. and Lee, J., "RP-DBSCAN: A Superfast Parallel DBSCAN Algorithm Based on Random Partitioning," In Proc. 2018 ACM Int'l Conf. on Management of Data (SIGMOD), Houston, Texas, June 2018. **...
DBSCAN对参数不敏感 查看答案
DBSCAN(*, eps=0.5, handle=None, min_samples=5, metric='euclidean', verbose=False, max_mbytes_per_batch=None, output_type=None, calc_core_sample_indices=True) DBSCAN 是一种非常强大且快速的聚类技术,可以找到数据集中的聚类。如果数据点倾向于聚集在更大的组中,这允许 DBSCAN 泛化到许多问题。
:param eps: Max distance to use for dbscan: :type eps: float: 例子: >>> import cudf >>> import clx.features >>> import clx.analytics.anomaly_detection >>> df = cudf.DataFrame( >>> { >>> "time": [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14], >>> "user"...