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( ', ' ) );
`