https://github.com/sumukh/parallelrf
Parallel Random Forests for digit classification. ~4000x speedup from original code
https://github.com/sumukh/parallelrf
Last synced: over 1 year ago
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Parallel Random Forests for digit classification. ~4000x speedup from original code
- Host: GitHub
- URL: https://github.com/sumukh/parallelrf
- Owner: Sumukh
- License: gpl-3.0
- Created: 2014-11-17T08:33:27.000Z (over 11 years ago)
- Default Branch: master
- Last Pushed: 2014-12-13T08:32:35.000Z (over 11 years ago)
- Last Synced: 2025-02-01T17:25:17.122Z (over 1 year ago)
- Language: C++
- Homepage:
- Size: 34.2 MB
- Stars: 2
- Watchers: 5
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
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lib Random Forest (libRF)
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Test Status:
[](https://travis-ci.org/Sumukh/ParallelRF)
Content:
1. Installing
2. Executing
3. References
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1. Installing
1.1 Dependencies
None except for STL.
1.2 Compiling libRandomForest
1.2.1 Linux/Mac
cd to the directory containing the libRF Makefile. Then type
$ make
which should result in an executable named prog.
1.2.2 Windows
For convenience we provide a Microsoft Visual Studio 2008 Solution file. Open the Visual Studio Solution and compile as usual.
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2. Executing
The command
$ ./prog
performs leave one out on the Ionosphere data set [2,3].
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3. References
[1] L. Breiman; Random Forests. Machine Learning, 45(1), 5-32, 2001
[2] V.G. Sigillito, S.P. Wing, L.V. Hutton, and K.B. Baker; Classification of radar returns from the ionosphere using neural networks. Johns Hopkins APL Technical Digest, 10, 262-266, 1989
[3] http://archive.ics.uci.edu/ml/datasets/Ionosphere