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https://github.com/ankane/vowpalwabbit-ruby
Fast online machine learning for Ruby
https://github.com/ankane/vowpalwabbit-ruby
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Fast online machine learning for Ruby
- Host: GitHub
- URL: https://github.com/ankane/vowpalwabbit-ruby
- Owner: ankane
- License: bsd-3-clause
- Created: 2019-10-21T20:52:09.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2024-07-27T04:10:36.000Z (3 months ago)
- Last Synced: 2024-10-04T11:59:16.089Z (about 1 month ago)
- Language: Ruby
- Homepage:
- Size: 37.1 KB
- Stars: 59
- Watchers: 6
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE.txt
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README
# Vowpal Wabbit Ruby
[Vowpal Wabbit](https://vowpalwabbit.org) - fast online machine learning - for Ruby
[](https://github.com/ankane/vowpalwabbit-ruby/actions)
## Installation
First, install the [Vowpal Wabbit C++ library](https://vowpalwabbit.org/start.html). For Homebrew, use:
```sh
brew install vowpal-wabbit
```
And for Ubuntu, use:
```sh
sudo apt install libvw0
```
Then add this line to your application’s Gemfile:
```ruby
gem "vowpalwabbit"
```
## Getting Started
Prep your data
```ruby
x = [[1, 2], [3, 4], [5, 6], [7, 8]]
y = [1, 2, 3, 4]
```
Train a model
```ruby
model = VowpalWabbit::Regressor.new(learning_rate: 100)
model.fit(x, y)
```
Use `VowpalWabbit::Classifier` for classification and `VowpalWabbit::Model` for other models
Make predictions
```ruby
model.predict(x)
```
Save the model to a file
```ruby
model.save("model.bin")
```
Load the model from a file
```ruby
model = VowpalWabbit::Regressor.load("model.bin")
```
Train online
```ruby
model.partial_fit(x, y)
```
Get the intercept and coefficients
```ruby
model.intercept
model.coefs
```
Score - R-squared for regression and accuracy for classification
```ruby
model.score(x, y)
```
## Parameters
Specify parameters
```ruby
model = VowpalWabbit::Model.new(cb: 4)
```
Supports the same parameters as the [CLI](https://github.com/VowpalWabbit/vowpal_wabbit/wiki/Command-Line-Arguments)
## Data
Data can be an array of arrays
```ruby
[[1, 2, 3], [4, 5, 6]]
```
Or a Numo array
```ruby
Numo::NArray.cast([[1, 2, 3], [4, 5, 6]])
```
Or an array of strings
```ruby
[
"0 | price:.23 sqft:.25 age:.05 2006",
"1 2 'second_house | price:.18 sqft:.15 age:.35 1976",
"0 1 0.5 'third_house | price:.53 sqft:.32 age:.87 1924"
]
```
Or a path to a file
```ruby
model.fit("train.txt")
model.partial_fit("train.txt")
model.predict("train.txt")
model.score("train.txt")
```
Files can be compressed
```ruby
model.fit("train.txt.gz")
```
Read more about the [input format](https://github.com/VowpalWabbit/vowpal_wabbit/wiki/Input-format)
## History
View the [changelog](https://github.com/ankane/vowpalwabbit-ruby/blob/master/CHANGELOG.md)
## Contributing
Everyone is encouraged to help improve this project. Here are a few ways you can help:
- [Report bugs](https://github.com/ankane/vowpalwabbit-ruby/issues)
- Fix bugs and [submit pull requests](https://github.com/ankane/vowpalwabbit-ruby/pulls)
- Write, clarify, or fix documentation
- Suggest or add new features
To get started with development:
```sh
git clone https://github.com/ankane/vowpalwabbit-ruby.git
cd vowpalwabbit-ruby
bundle install
bundle exec rake test
```