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https://github.com/yoch/svmloader
a very fast parser for sparse matrix at libsvm format
https://github.com/yoch/svmloader
fast libsvm-format loader python scipy sparse-data
Last synced: about 2 months ago
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a very fast parser for sparse matrix at libsvm format
- Host: GitHub
- URL: https://github.com/yoch/svmloader
- Owner: yoch
- License: gpl-3.0
- Created: 2016-12-13T00:02:04.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2017-11-13T15:43:53.000Z (about 7 years ago)
- Last Synced: 2024-10-31T08:42:07.783Z (2 months ago)
- Topics: fast, libsvm-format, loader, python, scipy, sparse-data
- Language: Python
- Homepage:
- Size: 1010 KB
- Stars: 10
- Watchers: 3
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
svmloader
=========
**svmloader** is a very fast python module (written in cython)
intended to load sparse data written at libsvm format.
It is not fully equivalent to `sklearn.datasets.load_svmlight_file`,
in particular `query_id` are not supported and `dtype` is restricted.
The types of data and labels are distinguished.
The labels types supported are `int` and `float` (default `int`),
and data can be parsed as `numpy.float64` or `numpy.float32` type (`float64` by default).
Compressed data in .gz or .bz2 format is supported as well.
Install
-------
Simply use `pip install svmloader`.
Alternatively, you can clone the repository and run `python setup.py install`.
Dependencies :
- numpy
- scipy
Documentation
-------------
See [here](http://svmloader.readthedocs.io/en/latest/).
Benchmarks
----------
Benchmarks on data taken from [libsvm datasets](https://www.csie.ntu.edu.tw/~cjlin/libsvmtools/datasets/).
| dataset *(shape, nonzeros)* | sklearn | svmloader |
| :--- | ---: | ---: |
| **mnist.scale** (60000x780, 8994156) | 78.1s | 1.5s |
| **rcv1_test.multiclass** (518571x47236, 33486015) | 1004.3s | 7.9s |