Dear all,

I am wondering if someone is aware of studies that compare different
classification system inducers on synthetic data with particular
features. Features might be: specific types of noise, data exhibiting
the Simpson paradox, non-linearly separable class distributions etc.
(any further ideas?)

Any pointers would be very much appreciated. Many thanks in advance!

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All the best
Chris