'use strict';

/**
* Latent Dirichlet Allocation via collapsed Gibbs sampling.
*
* @module @stdlib/nlp/lda
*
* @example
* var lda = require( '@stdlib/nlp/lda' );
*
* var words;
* 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 {}
*
* model.fit( 1000, 100, 10 );
*
* words = getTerms( 0, 3 );
* // returns e.g. [ { word: 'both', prob: ~0.0632 }, { word: 'pain', prob: ~0.0552 }, ... ]
*/

// MODULES //

var lda = require( './lda.js' );


// EXPORTS //

module.exports = lda;

'use strict';

/**
* Latent Dirichlet Allocation via collapsed Gibbs sampling.
*
* @module @stdlib/nlp/lda
*
* @example
* var lda = require( '@stdlib/nlp/lda' );
*
* var words;
* 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 {}
*
* model.fit( 1000, 100, 10 );
*
* words = getTerms( 0, 3 );
* // e.g., returns [ { word: 'both', prob: ~0.0632 }, { word: 'pain', prob: ~0.0552 }, ... ]
*/

// MODULES //

var lda = require( './lda.js' );


// EXPORTS //

module.exports = lda;

Fix non-deterministic return annotation