# ml-pipe

**Repository Path**: mirrors_mljs/ml-pipe

## Basic Information

- **Project Name**: ml-pipe
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2022-04-01
- **Last Updated**: 2026-03-22

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## 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