Back

Explore Courses Blog Tutorials Interview Questions
0 votes
2 views
in AI and Deep Learning by (50.2k points)

I'm implementing a nonlinear SVM and I want to test my implementation on a simple not linearly separable data. Google didn't help me find what I want. Can you please advise me where I can find such data. Or at least, how can I generate such data manually?

1 Answer

0 votes
by (108k points)

The particular data set you need will depend highly on your choice of the kernel function, so It seems the easiest method is simply creating a toy data set yourself.

Some helpful ideas:

  • Concentric circles
  • Spiral-shaped classes
  • Nested banana-shaped classes

If you just want a random data set that is not linearly separable, So for your query, you can use the iris data set. It is a multivariate data set where at least a couple of the classes in question are not linearly separable.

It's comprised of three classes, Class I is linearly separable from Class II and III; Class II and III are not linearly separable. If you want to use this data set, for convenience-sake you might prefer to remove Class I (approx. the first 50 data rows), so what remains is a two-class system, in which the two remaining classes are not linearly separable.

The iris data set is quite small (150 x 4, or 50 rows/class x four features)--depending on where you are with your SVM prototype testing, this might be exactly what you want, or you might want a larger data set.

If you wish to learn about Support Vector Machine then visit this Support Vector Machine Tutorial.

Welcome to Intellipaat Community. Get your technical queries answered by top developers!

30.5k questions

32.6k answers

500 comments

108k users

Browse Categories

...