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

Returns a copy of the value. Read more

Performs copy-assignment from source. Read more

Formats the value using the given formatter. Read more

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

This method tests for self and other values to be equal, and is used by ==. Read more

This method tests for !=.

Auto Trait Implementations

Blanket Implementations

Gets the TypeId of self. Read more

Immutably borrows from an owned value. Read more

Mutably borrows from an owned value. Read more

Compare self to key and return true if they are equal.

Returns the argument unchanged.

Calls U::from(self).

That is, this conversion is whatever the implementation of From<T> for U chooses to do.

The resulting type after obtaining ownership.

Creates owned data from borrowed data, usually by cloning. Read more

Uses borrowed data to replace owned data, usually by cloning. Read more

The type returned in the event of a conversion error.

Performs the conversion.

The type returned in the event of a conversion error.

Performs the conversion.