Could there be a difference between the words "feature", "attribute", and "decision variable" when used in the same paper? The one I am specifically thinking about is about an optimization method for clustering, but I am also wondering if there generally are any scenarios for which it could be.

I can't manage to google up an answer that either confirms or denies that these are the same thing, and I have no formal training in data science.


I left the article out at first to not omit a more general answer, but this is the link: ncbi.nlm.nih.gov/pmc/articles/PMC4532808

Some quotes:

  • "Mutation is a probabilistic operator that randomly modifies a decision variable of a candidate solution."
  • "Suppose [...] POPi(s) is the sth decision variable of POPi  (i.e.  C r t, t = 1,2,…, d  and  r = 1,2,…, q)."
  • "[...] max⁡(h i(SIV)),  min⁡(h i(SIV)) are the upper and lower bounds for each decision variable [...]"
  • "A SIV is a feature of the solution and can be imagined like a gene in GA."
  • $\begingroup$ You're right, it looked very cluttered as well. Thanks! $\endgroup$ Jul 19 '19 at 2:59
  • $\begingroup$ Please don't take papers in this journal too seriously... This is an Open Access journal, where anybody can publish almost anything for a fee $\endgroup$
    – HEKTO
    Jul 19 '19 at 14:20
  • $\begingroup$ @HEKTO I understand. Perhaps this is why I was reluctant to post the link in the first time - because my question is actually if there is a (conventional?) difference in general, but I just mentioned the article in case somebody wants an example. $\endgroup$ Jul 28 '19 at 4:09
  • $\begingroup$ The question you ask doesn't appear to be the question you want answered. "Could there be a difference...in the same paper?" is a broad question that asks whether it possible there exists any paper where there is a difference. That is probably too broad to admit an answer that is likely to be useful to others, and I'm not sure it is really about computer science. "Could there be a difference in this specific paper?" is a different question. "Is there a difference in this specific paper?" is yet another question. I suggest being precise about exactly what you want answered. $\endgroup$
    – D.W.

Feature and attribute have both the same meaning.

Decision variable is the variable which is used to make a split in a decision tree in tree based algorithms, i.e. the variable on which the decision is made.

  • 1
    $\begingroup$ Thanks for the reply, please see the article above though. It is not about decision trees. $\endgroup$ Jul 18 '19 at 3:15

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