/** * Construct a new cosine similarity function. * * @param damping The Bayesian damping term (added to denominator), to bias the * similarity towards 0 for low-cooccurance vectors. */ @Inject public CosineVectorSimilarity(@SimilarityDamping double damping) { Preconditions.checkArgument(damping >= 0, "negative damping not allowed"); dampingFactor = damping; }
@Inject public PearsonCorrelation(@SimilarityDamping double s) { Preconditions.checkArgument(s >= 0, "negative damping not allowed"); shrinkage = s; }
@Inject public SpearmanRankCorrelation(@SimilarityDamping double damping) { Preconditions.checkArgument(damping >= 0, "negative damping not allowed"); pearson = new PearsonCorrelation(damping); }
@Inject public PearsonCorrelation(@SimilarityDamping double s) { Preconditions.checkArgument(s >= 0, "negative damping not allowed"); shrinkage = s; }
/** * Construct a new cosine similarity function. * * @param damping The Bayesian damping term (added to denominator), to bias the * similarity towards 0 for low-cooccurance vectors. */ @Inject public CosineVectorSimilarity(@SimilarityDamping double damping) { Preconditions.checkArgument(damping >= 0, "negative damping not allowed"); dampingFactor = damping; }
@Inject public SpearmanRankCorrelation(@SimilarityDamping double damping) { Preconditions.checkArgument(damping >= 0, "negative damping not allowed"); pearson = new PearsonCorrelation(damping); }