Suppose you are given a data set consisting of nominal attributes, such as color, which takes values such as red, blue, green etc. can you use this data set directly to train an svm? if not, how will you transform a nominal attribute into a representation that can be used to train an svm? b. list a key similarity and a key difference between bagging and boosting.

Consider the following function main: int main() { int alpha[20]; int beta[20]; int matrix[10][4]; . . } a. write the definition of the function inputarray that prompts the user to input 20 numbers and stores the numbers into alpha. b. write the definition of the function doublearray that initializes the elements of beta to two times the corresponding elements in alpha. make sure that you prevent the function from modifying the elements of alpha. c. write the definition of the function copyalphabeta that stores alpha into the first five rows of matrix and beta into the last five rows of matrix. make sure that you prevent the function from modifying the elements of alpha and beta. d. write the definition of the function printarray that prints any onedimensional array of type int. print 15 elements per line. e. write a c11 program that tests the function main and the functions discussed in parts a through d. (add additional functions, such as printing a two-dimensional array, as needed.)

How to print: number is equal to: 1 and it is odd number number is equal to: 2 and it is even number number is equal to: 3 and it is odd number number is equal to: 4 and it is even number in the console using java using 1 if statement, 1 while loop, 1 else loop also using % to check odds and evens

How are stop motion special effects in animated films created