https://github.com/juliaai/learnapi.jl

A Julia interface for training and applying models in machine learning and statistics
https://github.com/juliaai/learnapi.jl

machine-learning-api

Last synced: 7 days ago
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A Julia interface for training and applying models in machine learning and statistics

• Host: GitHub
• URL: https://github.com/juliaai/learnapi.jl
• Owner: JuliaAI
• License: mit
• Created: 2022-07-27T23:29:43.000Z (over 2 years ago)
• Default Branch: dev
• Last Pushed: 2024-10-30T05:47:38.000Z (14 days ago)
• Last Synced: 2024-10-30T08:39:14.634Z (14 days ago)
• Topics: machine-learning-api
• Language: Julia
• Homepage:
• Size: 2.25 MB
• Stars: 34
• Watchers: 4
• Forks: 2
• Open Issues: 8
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# LearnAPI.jl

A base Julia interface for machine learning and statistics

[![Lifecycle:Maturing](https://img.shields.io/badge/Lifecycle-Maturing-007EC6)](ROADMAP.md)

[![Build Status](https://github.com/JuliaAI/LearnAPI.jl/workflows/CI/badge.svg)](https://github.com/JuliaAI/LearnAPI.jl/actions)

[![codecov](https://codecov.io/gh/JuliaAI/LearnAPI.jl/graph/badge.svg?token=9IWT9KYINZ)](https://codecov.io/gh/JuliaAI/LearnAPI.jl?branch=dev)

[![Docs](https://img.shields.io/badge/docs-dev-blue.svg)](https://juliaai.github.io/LearnAPI.jl/dev/)

Comprehensive documentation is [here](https://juliaai.github.io/LearnAPI.jl/dev/).

New contributions welcome. See the [road map](ROADMAP.md).

## Code snippet

Configure a machine learning algorithm:

```julia

julia> ridge = Ridge(lambda=0.1)

```

Inspect available functionality:

```

julia> LearnAPI.functions(ridge)

(:(LearnAPI.fit), :(LearnAPI.learner), :(LearnAPI.strip), :(LearnAPI.obs), 

:(LearnAPI.features), :(LearnAPI.target), :(LearnAPI.predict), :(LearnAPI.coefficients))

```

Train:

```julia

julia> model = fit(ridge, data)

```

Predict:

```julia

julia> predict(model, data)[1]

"virginica"

```

Predict a probability distribution ([proxy](https://juliaai.github.io/LearnAPI.jl/dev/kinds_of_target_proxy/#proxy_types) for the target):

```julia

julia> predict(model, Distribution(), data)[1]

UnivariateFinite{Multiclass{3}}(setosa=>0.0, versicolor=>0.25, virginica=>0.75)

```

## Credits

Created by Anthony Blaom, in cooperation with Cameron Bieganek and other [members of the

Julia

community](https://discourse.julialang.org/t/ann-learnapi-jl-proposal-for-a-basement-level-machine-learning-api/93048).