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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.
bst for 40,60,25,50,30,70,35,10,55,65,12
Write an algorithm to calculate a postfix expression. Execute your algorithm using the given postfix expression as your input : a b + c d +*f ↑ . T o evaluate a postfix expr
Q. Make the 11 item hash table resulting from hashing the given keys: 12, 44, 13, 88, 23, 94, 11, 39, 20, 16 and 5 by making use of the hash function h(i) = (2i+5) mod 11.
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How to measure the algorithm's efficiency? It is logical to examine the algorithm's efficiency as a function of some parameter n showing the algorithm's input size. Instance
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