How are the k-nearest neigh-bors (knn) algorithms different from k-means clustering?
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Consider the following algorithm, where the array A is indexed 1 through n: int add_them ( int n , int A[ ] ) { index i , j , k ; j = 0 ; for ( i = 1 ; i <= n ; i++) j = j + A[i] ; k = 1 ; for ( i = 1 ; i <= n ; i++) k = k + k ; return j + k ; } (a) If n = 5 and the array A contains 2, 5, 3, 7, and 8, what is returned? (b) What is the time complexity T(n) of the algorithm?
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How are the k-nearest neigh-bors (knn) algorithms different from k-means clustering?
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