nl_tokens: Use the model trained so far to classify a new sample .
pl_tokens: function ( sample , explain ) { var rankedLabelsWithExplain = this . ranker . classify ( sample , explain , /*withScores=*/ true ) ; var rankedLabels = ( explain > 0 ? rankedLabelsWithExplain . classes : rankedLabelsWithExplain ) ; var labelCountWithExplain = this . counter . classify ( sample , explain , /*withScores=*/ true ) ; var labelCount = ( explain > 0 ? labelCountWithExplain . <mask> [ 0 ] [ 0 ] : labelCountWithExplain [ 0 ] [ 0 ] ) ; if ( _ . isString ( labelCount ) ) labelCount = parseInt ( labelCount ) ; // Pick the labelCount most relevant labels from the list returned by the ranker:    var positiveLabelsWithScores = rankedLabels . slice ( 0 , labelCount ) ; var positiveLabels = positiveLabelsWithScores if ( positiveLabelsWithScores . length != 0 ) if ( _ . isArray ( positiveLabelsWithScores [ 0 ] ) ) var positiveLabels = positiveLabelsWithScores . map ( function ( labelWithScore ) { return labelWithScore [ 0 ] } ) ; return ( explain > 0 ? { classes : positiveLabels , explanation : { ranking : rankedLabelsWithExplain . explanation , counting : labelCountWithExplain . explanation } } : positiveLabels ) }