Extracting rules from a trained model about rseslib HOT 8 CLOSED

I'm afraid you are right. Needs to be added. For temporary solution you can use native implementation of rseslib.processing.classification.rules.roughset.RoughSetRuleClassifier with e.g. getRules(),toString().

from rseslib.

Thanks! As I already have a trained model is there a way to cast a weka.classifiers.rules.RoughSet to a rseslib.processing.classification.rules.roughset.RoughSetRuleClassifier? Or am I best starting from scratch with rseslib?

from rseslib.

Hi,

You need to start from scratch by training the native rseslib classifier. It needs to be fixed too.

Arek

from rseslib.

OK, no problem. Thank you both for all the help.

from rseslib.

Hi Ben,

Let us keep the issue open until it is fixed. We will fix it soon in master and close the issue then.

Arek

from rseslib.

Sorry about that! I have another question:

Thanks to your help I have trained a RoughSetRuleClassifier and extracted the rules. However, I can't work out how to extract the statistics for each rule (e.g. the support). getRules() returns a collection of Rule objects. I think I need RuleWithStatistics objects, but I don't know if it's possible to extract RuleWithStatistics objects from a RoughSetRuleClassifier. calculateStatistics() appears to only return the number of rules in the RoughSetRuleClassifier. Am I missing anything obvious?

from rseslib.

Each Rule object from the rough set classifier is actually EqulityDescriptorsRule which implements RuleWithStatistics interface. So you can just use casting:

Rule r = <a rule from rough set classifier>
((RuleWithStatistics)r).getSupport()

from rseslib.

That works perfectly, thank you.

from rseslib.