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Decision Tree - ID3 algorithm:
Imagine you only ever do one of the following four things for any weekend:
What you do depends on three factors: 1. weather (windy, rainy or sunny) 2. how much money you have (rich or poor) 3. whether your parents are visiting (yes or no) You say to yourself: if my parents are visiting, we'll go to the cinema. If they're not visiting and it's sunny, then I'll play tennis, and so on. Suppose we have the following instances in our (training) dataset: Weekend (Example) Weather Parents Money Decision (Category)
Apply the ID3 algorithm on this dataset to induce a decision tree. Note that I have written a function (readDataset.m) for reading the given dataset (MyWeekendDataset.txt) , you can use it to load the data and then write the algorithm. It is not necessary to show the decision tree graphically but please show the structure of the tree as well as you can.
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Binary: Each node has one, zero, or two children. This assertion creates many tree operations efficient and simple. Binary Search : A binary tree where each and every left
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Q. Explain that how do we implement two stacks in one array A[1..n] in such a way that neither the stack overflows unless the total number of elements in both stacks together is n.
Linear search is not the most efficient way to search an item within a collection of items. Though, it is extremely simple to implement. Furthermore, if the array elements are arra
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