关于python：DBSCAN处理大数据崩溃和内存错误

DBSCAN handling big data crashes and memory error

本问题已经有最佳答案，请猛点这里访问。

我正在对40万个数据点的数据集进行DBSCAN。这是我得到的错误：

1
2
3
4
5
6
7
8
9
10
11

Traceback (most recent call last):
File"/myproject/DBSCAN_section.py", line 498, in perform_dbscan_on_data
db = DBSCAN(eps=2, min_samples=5).fit(data)
File"/usr/local/Python/2.7.13/lib/python2.7/site-packages/sklearn/cluster/dbscan_.py", line 266, in fit
**self.get_params())
File"/usr/local/Python/2.7.13/lib/python2.7/site-packages/sklearn/cluster/dbscan_.py", line 138, in dbscan
return_distance=False)
File"/usr/local/Python/2.7.13/lib/python2.7/site-packages/sklearn/neighbors/base.py", line 621, in radius_neighbors
return_distance=return_distance)
File"sklearn/neighbors/binary_tree.pxi", line 1491, in sklearn.neighbors.kd_tree.BinaryTree.query_radius (sklearn/neighbors/kd_tree.c:13013)
MemoryError

我怎样才能解决这个问题？ DBSCAN处理大量数据有什么限制吗？

我的示例来源来自：http://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html

我的数据是X，Y坐标格式：

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16

11.342276,11.163416
11.050597,10.745579
10.798838,10.559784
11.249279,11.445535
11.385767,10.989214
10.825875,10.530120
10.598493,11.236947
10.571042,10.830799
11.454966,11.295484
11.431454,11.200208
10.774908,11.102601
10.602692,11.395169
11.324441,11.088243
10.731538,10.695864
10.537385,10.923226
11.215886,11.391537

我应该将数据转换为稀疏的CSR吗？怎么样？