An implementation of the voted-perceptron algorithm.
Project description
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 votedperceptron
Or install the development version from GitHub:
pip install git+https://github.com/bmgee/votedperceptron
Usage
On GitHub see examples/mnist_example.py for an MNIST digit classification example.
Release history Release notifications
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
| Filename, size | File type | Python version | Upload date | Hashes |
|---|---|---|---|---|
| Filename, size votedperceptron-1.0.0-py3-none-any.whl (12.2 kB) | File type Wheel | Python version py3 | Upload date | Hashes View hashes |
| Filename, size votedperceptron-1.0.0.tar.gz (13.5 kB) | File type Source | Python version None | Upload date | Hashes View hashes |
Close
Hashes for votedperceptron-1.0.0-py3-none-any.whl
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | d2044e0430a58bf1641e68635c006c790d6a9e4874b7ae47ddc1e799b8384293 |
|
| MD5 | 6a788d85a6bcbbb2b894ac734acfe98c |
|
| BLAKE2-256 | d28ffbc36c44b6ecc8172d010d42d342bca08084d81dfc594fb1be2598802848 |
