Given a feature vector, how to find whether my data points are linearly separable

Question

I have a feature vector in matrix notation, and I have data points in 2D plane. How to find whether my data points are linearly separable with that feature vector?

One can check whether there exists a line divides the data points into two. If there isn't a line, how to check for linear separability in higher dimensions?

score 0 · Accepted Answer · edited May 23 '17 at 12:06

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A theoretical answer

If we assume the samples of the two classes are distributed according to a Gaussian, we will get a quadratic function describing the decision boundary in the general case.

If the covariance matrices are identical we get a linear decision boundary.

A practical answer

See the SO discussion here.

edited May 23 '17 at 12:06

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answered Sep 03 '15 at 07:16

Michael Dorner

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Thank you, It is very much helpful. – John Smith Sep 03 '15 at 07:37

Given a feature vector, how to find whether my data points are linearly separable

1 Answers1

A theoretical answer

A practical answer