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# The ID3 algorithm is used to generate decision tree from the

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The ID3 algorithm is used to generate decision tree from the decision tree from the dataset. It is a recursive algorithm and in this there is a root node and to movefurther it splits the data to make its child node. If there is root node named as A the algorithm made a decision attribute fir the node A for each value of the attribute it gone to make its child node and whenever a new value for the attribute comes first it will put the attribute in the particular subset of the node A and then it checks the value of that attribute in all child node recursively. The decision tree made by this algorithm is used to classify new unseen test cases by working down the decision tree.The apriori algorithm is influential algorithm and it is used to for the concept of data mining. In this algorithm it made a subset of frequent item subset and the entire element in the subset should be individual frequent item set. To discuss thepseudo code of this algorithm Ck is the candidate item set of size k and Lk is the frequent item set of size k. And then we run a loop from 1 to the size of frequent item set maximum value and for each value of k increment the value of candidate item set that is Ck value of Lk+1 becomes equal to value of Ck+1 with the minimum support and after completing the loop return the value of Lk.

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