We had an attribute Time which specifieswhen the class begins (a) We can pick a thresholdand use (Time ) as a criteria to split the data in two Explainhow you might pick the optimal value of (b) In the decision tree learning algorithm discussed in class, once an binary attribute is used, thesubtrees do not need to consider it Explain why when there are continuous attributes this maynot be the case

Question: We had an attribute Time which specifieswhen the class begins. (a) We can pick a thresholdand use (Time < )? as a criteria to split

We had an attribute “Time” which specifieswhen the class begins.

(a) We can pick a thresholdτand use (Time< τ)? as a criteria to split the data in two. Explainhow you might pick the optimal value of τ.

(b) In the decision tree learning algorithm discussed in class, once an binary attribute is used, thesubtrees do not need to consider it. Explain why when there are continuous attributes this maynot be the case.

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