Handbook on Computational Intelligence by Plamen Parvanov Angelov

Author:Plamen Parvanov Angelov
Language: eng
Format: epub
ISBN: 9789814675024
Publisher: World Scientific Publishing Co Pte Ltd
Published: 2016-03-18T00:00:00+00:00

Separating property of the Kernel LDA method is illustrated in Figure 13.6.

Figure 13.6: Kernel LDA projection example. Chart on the left demonstrates the distribution of the data in the initial space. Right chart demonstrates the histogram of the data samples projected on optimal vector in the feature map space.

13.3.5. Kernelization of an Arbitrary Linear Model

In fact, any linear model can be “kernelized” by replacing inner products 〈x, t〉 with kernel values K(x, t). Here, we show the idea on an example of the ridge regression model. Recall the classical ridge regression with target function

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