https://github.com/mljs/ml-pipe
https://github.com/mljs/ml-pipe
Last synced: 4 months ago
JSON representation
- Host: GitHub
- URL: https://github.com/mljs/ml-pipe
- Owner: mljs
- License: mit
- Created: 2022-03-08T12:36:58.000Z (over 3 years ago)
- Default Branch: main
- Last Pushed: 2023-02-13T14:25:17.000Z (over 2 years ago)
- Last Synced: 2025-02-15T09:11:28.822Z (4 months ago)
- Language: TypeScript
- Homepage: https://mljs.github.io/ml-pipe/
- Size: 170 KB
- Stars: 2
- Watchers: 3
- Forks: 0
- Open Issues: 11
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
Awesome Lists containing this project
README
# ml-pipe
[![NPM version][npm-image]][npm-url]
[![build status][ci-image]][ci-url]
[![Test coverage][codecov-image]][codecov-url]
[![npm download][download-image]][download-url]
Orchestrate ML pipelines. One design different to `sklearn` pipelines is that our transformers can have the attribute `onTarget` for use in Pipelines. There, it can be convenient and to simply add a target transformation as a step into the Pipeline
## Installation
`$ npm i ml-pipe`
## Usage
```js
import { trainTestSplit } from 'ml-pipe/modelSelection/trainTestSplit';
import {Pipeline} from 'ml-pipe/pipeline';
import {FCNN} from 'ml-pipe/estimators/neuralNetwork/fcnn'
import {StandardScaler, TargetStandardScaler} from 'ml-pipe/transformers/preprocessing/standardScaler'
import {meanSquaredError} from 'ml-pipe/metrics/regression'
const {xTrain, xTest, yTrain, yTest} = trainTestSplit(x, y,
{trainFraction: 0.8, stratify: yBinned})
const pipe = new Pipeline([
{
'name': 'xScale',
'object': new StandardScaler()
},
{
'name': 'yScale',
'object': new TargetStandardScaler()
},
{
'name': 'model',
'object': new FCNN({inputSize: 5})
}
])
await pipe.fit(XTrain, yTrain)
const predictionsTest = pipe.predict(xTest)
const mse = meanSquaredError(predictionsTest, yTest)
```
## Related package:
- [scikit.js](https://github.com/javascriptdata/scikit.js)
## License
[MIT](./LICENSE)
[npm-image]: https://img.shields.io/npm/v/ml-pipe.svg
[npm-url]: https://www.npmjs.com/package/ml-pipe
[ci-image]: https://github.com/kjappelbaum/ml-pipe/workflows/Node.js%20CI/badge.svg?branch=main
[ci-url]: https://github.com/kjappelbaum/ml-pipe/actions?query=workflow%3A%22Node.js+CI%22
[codecov-image]: https://img.shields.io/codecov/c/github/kjappelbaum/ml-pipe.svg
[codecov-url]: https://codecov.io/gh/kjappelbaum/ml-pipe
[download-image]: https://img.shields.io/npm/dm/ml-pipe.svg
[download-url]: https://www.npmjs.com/package/ml-pipe