Decision treesplease see the attchment for the questions. we need the soultion before mid night today 2/6/2022 HW01: Decision treesRemember that only PDF submissions are accepted.1. How many decision trees are there with 3 binary attributes? With 4?2. In class we looked at an example where all the attributes were binary (i.e., yes/no valued). Consideran example where instead of the attribute “Morning?", we had an attribute “Time" which specifieswhen the class begins.(a) We can pick a threshold T and use (Time < T)? as a criteria to split the data in two. Explainhow you might pick the optimal value of T.(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.3. Give two reasons why memorizing the training data and doing table lookups is a bad strategy forlearning.4. (Programming) You need to implement the decision tree algorithm as in the slides. The data we usefor binary classification tasks is the UCI a4a data.https://www.csie.ntu.edu.tw/-cjlin/libsvmtools/datasets/binary.html#a4a You need to report themisclassification error to measure the prediction accuracy rate. You can reuse the code to this questionin your mini-project and play with more data then.

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Decision trees

please see the attchment for the questions. we need the soultion before mid night today 2/6/2022

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Decision trees are there with 3 binary attributes:-------------
For three attributes there are 7 nodes in the tree, i.e., for n = 3, number of nodes = 2³-1.
Similarly, if we have n attributes, there are 2ⁿ - 1 nodes (approx.)
Decision trees are there with n binary attributes = _2²ⁿ
So, for 3 binary attributes = _2²³ = 2⁸ = 256 Decision trees

Decision trees are there with 4 binary attributes:-------------
For three attributes there are 15 nodes in the tree, i.e., for n = 4, number of nodes = 2⁴-1.
Similarly, if we have n attributes, there are 2ⁿ - 1 nodes (approx.)
Decision trees are there with n binary attributes = _2²ⁿ
So, for 3 binary attributes = _2²⁴ = 2¹⁶ = 65,536 Decision trees