@stdlib/nlp-lda

Latent Dirichlet Allocation via collapsed Gibbs sampling.

Science Score: 44.0%

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Low similarity (14.8%) to scientific vocabulary

Keywords

bayesian clustering javascript learning mcmc mixed-membership model nlp node node-js nodejs stdlib text-mining topic unsupervised

Last synced: 6 months ago · JSON representation ·

Repository

Latent Dirichlet Allocation via collapsed Gibbs sampling.

Basic Info

Host: GitHub
Owner: stdlib-js
License: apache-2.0
Language: JavaScript
Default Branch: main
Homepage: https://github.com/stdlib-js/stdlib
Size: 2.59 MB

Statistics

Stars: 9
Watchers: 4
Forks: 0
Open Issues: 0
Releases: 0

Topics

bayesian clustering javascript learning mcmc mixed-membership model nlp node node-js nodejs stdlib text-mining topic unsupervised

Created over 4 years ago · Last pushed 9 months ago

Metadata Files

Readme Changelog Contributing License Code of conduct Citation Security

We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.

The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.

When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.

To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!

LDA

Latent Dirichlet Allocation via collapsed Gibbs sampling.

## Installation ```bash npm install @stdlib/nlp-lda ``` Alternatively, - To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]). - If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions). - For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]). The [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships. To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

## Usage ```javascript var lda = require( '@stdlib/nlp-lda' ); ``` #### lda( docs, K\[, options] ) [Latent Dirichlet Allocation][lda] via collapsed Gibbs sampling. To create a model, call the `lda` function by passing it an `array` of `strings` and the number of topics `K` that should be identified. ```javascript var model; var docs; docs = [ 'I loved you first', 'For one is both and both are one in love', 'You never see my pain', 'My love is such that rivers cannot quench', 'See a lot of pain, a lot of tears' ]; model = lda( docs, 2 ); // returns {} ``` After initialization, model parameters are estimated by calling the `.fit()` method, which performs collapsed Gibbs sampling. The model object contains the following methods: #### model.fit( iter, burnin, thin ) ```javascript model.fit( 1000, 100, 10 ); ``` The `iter` parameter denotes the number of sampling iterations. While a common choice, one thousand iterations might not always be appropriate. Empirical diagnostics can be used to assess whether the constructed Markov Chain has converged. `burnin` denotes the number of estimates that are thrown away at the beginning, whereas `thin` controls the number of estimates discarded in-between iterations. #### model.getTerms( k\[, no = 10] ) Returns the `no` terms with the highest probabilities for chosen topic `k`. ```javascript var words = model.getTerms( 0, 3 ); /* returns [ { 'word': 'both', 'prob': 0.06315008476532499 }, { 'word': 'pain', 'prob': 0.05515729517235543 }, { 'word': 'one', 'prob': 0.05486669737616135 } ] */ ```

## Examples ```javascript var sotu = require( '@stdlib/datasets-sotu' ); var roundn = require( '@stdlib/math-base-special-roundn' ); var stopwords = require( '@stdlib/datasets-stopwords-en' ); var lowercase = require( '@stdlib/string-lowercase' ); var lda = require( '@stdlib/nlp-lda' ); var speeches; var words; var terms; var model; var str; var i; var j; words = stopwords(); for ( i = 0; i < words.length; i++ ) { words[ i ] = new RegExp( '\\b'+words[ i ]+'\\b', 'gi' ); } speeches = sotu({ 'range': [ 1930, 2010 ] }); for ( i = 0; i < speeches.length; i++ ) { str = lowercase( speeches[ i ].text ); for ( j = 0; j < words.length; j++ ) { str = str.replace( words[ j ], '' ); } speeches[ i ] = str; } model = lda( speeches, 3 ); model.fit( 1000, 100, 10 ); for ( i = 0; i <= 80; i++ ) { str = 'Year: ' + (1930+i) + '\t'; str += 'Topic 1: ' + roundn( model.avgTheta.get( i, 0 ), -3 ) + '\t'; str += 'Topic 2: ' + roundn( model.avgTheta.get( i, 1 ), -3 ) + '\t'; str += 'Topic 3: ' + roundn( model.avgTheta.get( i, 2 ), -3 ); console.log( str ); } terms = model.getTerms( 0, 20 ); for ( i = 0; i < terms.length; i++ ) { terms[ i ] = terms[ i ].word; } console.log( 'Words most associated with first topic:\n ' + terms.join( ', ' ) ); terms = model.getTerms( 1, 20 ); for ( i = 0; i < terms.length; i++ ) { terms[ i ] = terms[ i ].word; } console.log( 'Words most associated with second topic:\n ' + terms.join( ', ' ) ); terms = model.getTerms( 2, 20 ); for ( i = 0; i < terms.length; i++ ) { terms[ i ] = terms[ i ].word; } console.log( 'Words most associated with third topic:\n ' + terms.join( ', ' ) ); ```

* * * ## Notice This package is part of [stdlib][stdlib], a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more. For more information on the project, filing bug reports and feature requests, and guidance on how to develop [stdlib][stdlib], see the main project [repository][stdlib]. #### Community [![Chat][chat-image]][chat-url] --- ## License See [LICENSE][stdlib-license]. ## Copyright Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].

Owner

Name: stdlib
Login: stdlib-js
Kind: organization

Website: https://stdlib.io
Twitter: stdlibjs
Repositories: 3,692
Profile: https://github.com/stdlib-js

Standard library for JavaScript.

Citation (CITATION.cff)

cff-version: 1.2.0
title: stdlib
message: >-
  If you use this software, please cite it using the
  metadata from this file.

type: software

authors:
  - name: The Stdlib Authors
    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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Avg Commits per committer: 47.0
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Total versions: 10
Total maintainers: 4

npmjs.org: @stdlib/nlp-lda

Latent Dirichlet Allocation via collapsed Gibbs sampling.

Homepage: https://stdlib.io
License: Apache-2.0
Latest release: 0.2.1
published almost 2 years ago

Versions: 10
Dependent Packages: 2
Dependent Repositories: 1
Downloads: 20 Last month

Rankings

Dependent packages count: 8.9%

Dependent repos count: 10.3%

Stargazers count: 10.5%

Average: 12.4%

Forks count: 15.4%

Downloads: 17.0%

Maintainers (4)

planeshifter rreusser stdlib-bot kgryte

Funding

type: opencollective
url: https://opencollective.com/stdlib

Last synced: 6 months ago

Dependencies

package.json npm

@stdlib/datasets-sotu ^0.0.x development
@stdlib/datasets-stopwords-en ^0.0.x development
@stdlib/math-base-special-roundn ^0.0.x development
@stdlib/string-lowercase ^0.0.x development
istanbul ^0.4.1 development
tap-spec 5.x.x development
tape git+https://github.com/kgryte/tape.git#fix/globby development
@stdlib/array-float64 ^0.0.x
@stdlib/array-int32 ^0.0.x
@stdlib/assert-contains ^0.0.x
@stdlib/assert-has-own-property ^0.0.x
@stdlib/assert-is-nonnegative-integer ^0.0.x
@stdlib/assert-is-plain-object ^0.0.x
@stdlib/assert-is-positive-integer ^0.0.x
@stdlib/assert-is-positive-number ^0.0.x
@stdlib/assert-is-string-array ^0.0.x
@stdlib/math-base-special-floor ^0.0.x
@stdlib/nlp-tokenize ^0.0.x
@stdlib/random-base-randu ^0.0.x
@stdlib/string-format ^0.0.x
@stdlib/utils-define-nonenumerable-read-only-property ^0.0.x
@stdlib/utils-define-read-only-property ^0.0.x

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@stdlib/nlp-lda

Science Score: 44.0%

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LDA

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