PCA Predictor TODO

Labels / Tags

  • Predictor
  • Dimension reduction

Principle

Project queries onto reduced space of dimension d given the PCAModel obtains from PCA dimension reduction algorithm.

Scalability

The computational complexity for a $d$ dimentional query and the d\ x\ p matrix PCAModel

Input

Single query

A numerical vector value.

Multiple queries, i.e collection of data observations

A collection of numerical vector value.

Parameters

1 : KMeansModel

KMeansModel contains the list of prototypes returned by KMeans algorithm.

Output

Single query

Returns the ClusterId of the closest $K$MeansModel prototype.

Multiple queries, i.e. a collection of queries of numerical vectors

Returns the HardClustering associates to input data.

Associate visualizations

  • HardClustering

Practical strategies

Business case

Usage