"declared id attributes used in clustering?"
pep
New Altair Community Member
Hi, can anyone help with the following questions pls?
Is a (numeric) attribute whose role is declared to be id, used by default by the software in building clusters (by the attribute participating in the computation of distances. etc)? What about building a supervised learning model as a:
- decision tree - does the implemented algorithm compute by default the gain ratio for an id attribute?
- naive bayes classifiers - does the algorithm compute conditional probabilities (and implicitly sample means and standard deviations) in the case of the declared id attribute?
cheers
Is a (numeric) attribute whose role is declared to be id, used by default by the software in building clusters (by the attribute participating in the computation of distances. etc)? What about building a supervised learning model as a:
- decision tree - does the implemented algorithm compute by default the gain ratio for an id attribute?
- naive bayes classifiers - does the algorithm compute conditional probabilities (and implicitly sample means and standard deviations) in the case of the declared id attribute?
cheers
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Answers
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Hi,
no, in general, attributes with the role "id" are only used for identification purposes like in the plotters but never for data mining schemes. For modeling, usually only the regular attributes (i.e. no specific role), the label, and sometimes the weight are used.
whose role is declared to be id, used by default by the software in building clusters (by the attribute participating in the computation of distances. etc)?
Same here as for clustering.
What about building a supervised learning model as a:
No, this will not happen.
- decision tree - does the implemented algorithm compute by default the gain ratio for an id attribute?
Dito.
- naive bayes classifiers - does the algorithm compute conditional probabilities (and implicitly sample means and standard deviations) in the case of the declared id attribute?
Cheers,
Ingo0
