Data Reduction with Principal Component Analysis (PCA)ΒΆ

Non-Causal Step

This step applies the Principal Component Analysis algorithm to search for orthogonal bases that best represent the data. Using these orthogonal bases, the original data can be projected onto a much smaller space. The size of the original data can be significantly reduced in this way.

Input Parameters

  1. Normalized input data (large size)

Output Parameters

  1. Reduced data set

Workflow

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Algorithm

Principal Component Analysis

References

    1. Han, M. Kamber and J. Pei, Data Mining - Concepts and Techniques, 3rd ed., Amsterdam: Morgan Kaufmann Publishers, 2012.