pub struct PcaParams { /* private fields */ }
Expand description

Pincipal Component Analysis parameters

Implementations

Apply whitening to the embedding vector

Whitening will scale the eigenvalues of the transformation such that the covariance will be unit diagonal for the original data.

Trait Implementations

Fit a PCA model given a dataset

The Principal Component Analysis takes the records of a dataset and tries to find the best fit in a lower dimensional space such that the maximal variance is retained.

Parameters

  • dataset: A dataset with records in N dimensions

Returns

A fitted PCA model with origin and hyperplane

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