Suppose you are given the following multi-class classification training data, where each input example has three features and output label takes a value from good, bad, and ugly. • x1=(0, 1, 0) and y1=good • x2=(1, 0, 1) and y2=bad • 13=(1, 1, 1) and y3=ugly • x4=(1, 0, 0) and y4=bad • 15=(0, 0, 1) and y5=good

Let's revisit our first problem, where we want to set up a series of chess matches so we can rank six players in our class. As we did before, we will assume that everyone keeps their chess rating a private secret; however, when two players have a chess match, the person with the higher rating wins 100% of the time. But this time, we are only interested in identifying the BEST of these six players and the WORST of these six players. (We don't care about the relative ordering or ranking of the middle four players.) Your goal is to devise a comparison-based algorithm that is guaranteed to identify the player with the highest rating and the player with the lowest rating. Because you are very strong at Algorithm Design, you know how to do this in the most efficient way. Here are five statements. A. There exists an algorithm to solve this problem using 6 matches, but there does not exist an algorithm using only 5 matches. B. There exists an algorithm to solve this problem using 7 matches,…

Merge sort: what is its efficiency if the number of chocolates and students increases significantly. Also, what is the complexity analysis ( T(n) and O(n) ).   Iterative and recursive function: to distribute a given set of x to y, what is the complexity analysis ( T(n) and O(n) ) and which is better.

An ordinary ruler is a straight piece of wood where distances 0, 1, 2 . . . , N are marked, for some N ≥ 1. A sparse ruler (or simply a ruler ) is an ordinary ruler from which some of the numbers 1, . . . , N −1 may have been deleted. The number of marks on the ruler is its order and the value N is its reach. Here, we will represent a ruler as a Python list of strictly increasing integers starting with 0. For instance [0,1,3,7] is a ruler of order 4 and reach 7. A sparse ruler of reach N is complete if it is possible to measure all distances between 1 and N by taking the dierences between two marks. For instance [0,1,3] is complete because the pairs (0, 1), (1, 3), and (0, 3) yield distances of 1, 2, and 3 respectively. (Note that the pair of marks do not need to be consecutive.) On the other hand, [0,1,4] is not complete as there is no way to measure a distance of 2. could you please provide the code for this question in python , the parts in bold explain some of the concepts in this…