# LearnKit
Elixir package for machine learning
Available algorithms:
- K-Nearest Neighbours
## Installation
If [available in Hex](https://hex.pm/docs/publish), the package can be installed
by adding `learn_kit` to your list of dependencies in `mix.exs`:
```elixir
def deps do
[
{:learn_kit, "~> 0.1.0"}
]
end
```
### K-Nearest Neighbours
Initialize classificator with data set consists from labels and features:
```elixir
classificator = LearnKit.Knn.new
|> LearnKit.Knn.add_train_data({:a1, [-1, -1]})
|> LearnKit.Knn.add_train_data({:a1, [-2, -1]})
|> LearnKit.Knn.add_train_data({:a1, [-3, -2]})
|> LearnKit.Knn.add_train_data({:a2, [1, 1]})
|> LearnKit.Knn.add_train_data({:a2, [2, 1]})
|> LearnKit.Knn.add_train_data({:a2, [3, 2]})
|> LearnKit.Knn.add_train_data({:a2, [-2, -2]})
```
Predict label for new feature:
```elixir
LearnKit.Knn.classify(classificator, [feature: [-1, -2], k: 3, weight: "distance"])
```
feature - new feature for prediction, required
k - number of nearest neighbors, optional, default - 3
algorithm - algorithm for calculation of distances, one of the [brute], optional, default - "brute"
weight - method of weighted neighbors, one of the [uniform|distance], optional, default - "uniform"
## Contributing
Bug reports and pull requests are welcome on GitHub at https://github.com/kortirso/elixir_learn_kit.
## License
The package is available as open source under the terms of the [MIT License](http://opensource.org/licenses/MIT).
## Disclaimer
Use this package at your own peril and risk.
## Documentation
Documentation can be generated with [ExDoc](https://github.com/elixir-lang/ex_doc)
and published on [HexDocs](https://hexdocs.pm). Once published, the docs can
be found at [https://hexdocs.pm/learn_kit](https://hexdocs.pm/learn_kit).