In the context of clustering in machine learning, k-means clustering algorithm groups data points based on similarity. While there are various methods to quantify distance between data points, we discussed a particular method, Euclidean Distance in class. Customers Variable 1 Variable 2 A 1 4 B 5 6 C 3 4 Calculate the approximate Euclidean Distance between Customer A and B. 2.78 3.14 5.12 6.03 4.47

Given numbers = (66, 74, 83, 87, 89, 40, 32, 77), pivot = 32 What is the low partition after the partitioning algorithm is completed? What is the high partition after the partitioning algorithm is completed?

Describe the benefits of using the merge sort in Java. What are the key steps that must be taken to ensure an efficient sorting of objects? Also, specifically think of and give a real-life scenario where Merge sort may be used Merge sort may be a better fit than Quick and Radix sorts

In computing gcd(125, 332) using Euclid's GCD algorithm, the pair (¿[0], k[0]) = (125,332) is replaced by the pair (j[1], k[1]) after the first iteration. Enter your answer for (j[1], k[1]) in the box below as a comma-separated list. For example, if your answer is (1, 2), then enter 1, 2 (without parenthesis). (j[1], k[1]) = ( Next, finish the algorithm to determine gcd(125, 332). gcd(125, 332) =