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I was given a decision tree with sample data in class to solve. After computing the gaining/splitting tree with the sample data provided, I ended up with the same tree that was in the question.

If I ended up with the same tree that was given in the question does that mean there is no more information gain and everything is classified properly?

I just want to know the concept behind, what if the decision tree that was given to us ended up being the same as my solution.

John Coleman
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user8788665
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  • Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. Avoid asking multiple distinct questions at once. See the How to Ask page for help clarifying this question. – Mickael Oct 17 '17 at 08:47
  • Hope I narrowed down my question. – user8788665 Oct 17 '17 at 09:02

1 Answers1

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The person who has given you the decision tree has already done the calculation with the example data.

Was the task you have to do to create a new decision tree or should you just check how good the given decission tree (e.g. confusion matrix) is?

cronoik
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  • The question was divided into two parts. 1st part was to check if the given tree matched with the sample data. 2nd part was to create a decesion tree using the sample data with I had ended up with the same tree. (No confusion mateix) I just want to know what it means if we end up with the same data. Does that mean no information gain? – user8788665 Oct 17 '17 at 08:58