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    ml-dataset-metadata

    0.3.0 • Public • Published

    dataset-metadata

    NPM version build status Test coverage David deps npm download

    a class to manipulate metadata for statistical analysis

    Installation

    $ npm i dataset-metadata

    API Documentation

    Examples

    to import the package use

    const METADATA = require('dataset-metadata');

    or

    import { METADATA } from 'ml-dataset-metadata';

    to create a metadata object use

    import { getClasses } from 'ml-dataset-iris';
    const metadata = getClasses();
    let L = new METADATA([metadata], { headers: ['iris'] });

    this will create an array with the class of the famous iris dataset and create a METADATA object L.

    List all the available metadata

    L.list()

    returns an array with all the metadata headers.

    Retrieve information (number of classes, counts for each classes) about a particular metadata using

    L.get('iris');

    Retrieve values of a particular metadata as a Matrix object. This will coerce any string class into a Matrix of number with first class being "0", second being "1", etc.

    L.get('iris', { format: 'matrix' }).values

    For supervised method it is usual to sample a class to get a training set and a test set.

    L.sample('iris')

    returns an object with four arrays: trainIndex, testIndex, mask (a boolean filter), and classVector (the original class).

    To append another metadata.

    let newMetadata = metadata;
    L.append(NewMetadata, 'column', { header: 'duplicated' });

    To remove the duplicated metadata.

    L.remove('duplicated', 'column');

    Import and export METADATA object.

    let L = new METADATA([metadata], { headers: ['iris'] });
        L = JSON.stringify(L.toJSON());
        let newL = METADATA.load(JSON.parse(L));

    License

    MIT

    Keywords

    none

    Install

    npm i ml-dataset-metadata

    DownloadsWeekly Downloads

    0

    Version

    0.3.0

    License

    MIT

    Unpacked Size

    95.6 kB

    Total Files

    7

    Last publish

    Collaborators

    • jwist