Manifold.MDS

Multidimensional scaling using classical MDS algorithm.

Classical MDS converts a distance matrix into a centered similarity matrix and computes its dominant eigenvectors to recover coordinates that preserve the original pairwise dissimilarities.

interface MDSOptions {
    nComponents?: number;
    dissimilarity?: 'euclidean' | 'precomputed';
}
constructor(options: MDSOptions = {})

Options

• nComponents (number, default 2): dimension of the embedded space.
• dissimilarity ('euclidean' | 'precomputed', default 'euclidean'): if 'precomputed', the input to fitTransform should be a distance matrix.

fitTransform(data: number[][]): number[][] computes the embedding and returns it.

getEmbedding(): number[][] returns the computed embedding.