GitHub user mengxr opened a pull request:
https://github.com/apache/spark/pull/117
[MLLIB-18] [WIP] Adding sparse data support and update KMeans
Continue our discussions from
https://github.com/apache/incubator-spark/pull/575
This PR is WIP because it depends on a SNAPSHOT version of breeze.
Per previous discussions and benchmarks, I switched to breeze for linear
algebra operations. @dlwh and I made some improvements to breeze to keep its
performance comparable to the bare-bone implementation, including norm
computation and squared distance. This is why this PR needs to depend on a
SNAPSHOT version of breeze.
@fommil , please find the notice of using netlib-core in `NOTICE`. This is
following Apache's instructions on appropriate labeling.
I'm going to update this PR to include:
1. Fast distance computation: using `\|a\|_2^2 + \|b\|_2^2 - 2 a^T b` when
it doesn't introduce too much numerical error. The squared norms are
pre-computed. Otherwise, computing the distance between the center (dense) and
a point (possibly sparse) always takes O(n) time.
2. Some numbers about the performance.
3. A released version of breeze. @dlwh, a minor release of breeze will help
this PR get merged early. Do you mind sharing breeze's release plan? Thanks!
You can merge this pull request into a Git repository by running:
$ git pull https://github.com/mengxr/spark sparse-kmeans
Alternatively you can review and apply these changes as the patch at:
https://github.com/apache/spark/pull/117.patch
To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:
This closes #117
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commit 07ffaf2b7f3300a6c0afc2a21a0134c76d3ec8dc
Author: Xiangrui Meng <m...@databricks.com>
Date: 2014-03-10T21:27:46Z
add dense/sparse vector data models and conversions to/from breeze vectors
use breeze to implement KMeans in order to support both dense and sparse
data
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