An implementation of the voted perceptron algorithm described in the publication below:
%0 Journal Article %D 1999 %@ 0885-6125 %J Machine Learning %V 37 %N 3 %R 10.1023/A:1007662407062 %T Large Margin Classification Using the Perceptron Algorithm %U http://dx.doi.org/10.1023/A%3A1007662407062 %I Kluwer Academic Publishers %8 1999-12-01 %A Freund, Yoav %A Schapire, RobertE. %P 277-296 %G English
Installation
Install the current PyPI release:
pip install votedperceptronOr install the development version from GitHub:
pip install git+https://github.com/bmgee/votedperceptronUsage
On GitHub see examples/mnist_example.py for an MNIST digit classification example.
1 maintainer
Release files for votedperceptron 1.0.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| votedperceptron-1.0.0.tar.gz | 13.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| votedperceptron-1.0.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 25.7 kB
Release files / votedperceptron-1.0.0.tar.gz
| Download URL | votedperceptron-1.0.0.tar.gz |
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| Size | 13.5 kB |
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Release files / votedperceptron-1.0.0-py3-none-any.whl
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| Size | 12.2 kB |
| Tags | Python 3 |
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