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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.
/* the program accepts two polynomials as a input & prints the resultant polynomial because of the addition of input polynomials*/ #include void main() { int poly1[6][
A graph with n vertices will absolutely have a parallel edge or self loop if the total number of edges is greater than n-1
What data structure would you mostly likely see in a nonrecursive execution of a recursive algorithm? Stack
24 56 47 35 10 90 82 31
Program segment for deletion of any element from the queue delete() { int delvalue = 0; if (front == NULL) printf("Queue Empty"); { delvalue = front->value;
null(nil) = true // nil refer for empty tree null(fork(e, T, T'))= false // e : element , T and T are two sub tree leaf(fork(e, nil, nil)) = true leaf(
Q. Write a procedure to the insert a node into the linked list at a particular position and draw the same by taking an example?
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Explain an efficient way of storing a sparse matrix in memory. A matrix in which number of zero entries are much higher than the number of non zero entries is called sparse mat
perform the following length operation LENGTH("welcome to ICA")=
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