Given a set of three points, -2, 0, and 9, we want to use k- Means Clustering with k = 2 to cluster them into two clusters. If the initial cluster centers are C1 = -4.0 and C2 = 2.0, What will be the center of C1 after completing first iteration of k means clustering algorithm?

Q: O In a population map of the U over 1 million. O In a population map of the U

A: 1. clustering algorithm cannot be used for estimation and hence this question is not answerable…

Q: Suppose we cluster a set of N data points using two different using the k-means clustering algorithm…

A: Suppose we cluster a set of N data points using two different using the k-means clusteringalgorithm…

Q: Which of the following statements about the K-means algorithm are correct? Group of answer choices…

A: The K-means algorithm is a clustering technique that seeks to partition a set of data points into a…

Q: You want to cluster 7 points into 3 clusters using the k-Means Clusteringalgorithm. Suppose after…

A: refer to answer

Q: In the context of clustering in machine learning, k-means clustering algorithm groups data points…

A: The study of algorithms and statistical models that allow computer systems to learn from their…

Q: We will create this vocabulary by randomly selecting tens or hundreds of thousands of local features…

A: In the context of image processing and computer vision, the concept of a "Bag of Visual Words" or…

Q: Practice problem: use DFS version of topological sort for the following DAG J6 DFS(G) I for each…

A: Topological_Sort: The graph is passed to DFG(G) function. Each vertex is checked for white colour.…

Q: What is the code in R studio to make an elbow chart to find the optimal value of k in k- means…

A: WE have to write a code For R studio to find the optimal value of k

Q: What are the centroids of the following set of values if we cluster them using 2 means algorithm?…

A:

Q: Compute the cost of r JOINA=B s using the method of index loops with an index of height 2 on B of s.…

A: ANSWER: Index Loop Method:

Q: We will create this vocabulary by randomly selecting tens or hundreds of thousands of local features…

A: We will create this vocabulary by randomly selecting tens or hundreds of thousands of local features…

Q: Question 1 In the previous example, the K-Means algorithm was able to accurately find the three…

A: Task : Perform K-means clustering on the toy dataset. the clustering is performed using sklearn…

Q: True or False: When we use k means clustering method to find the best clusters for the chosen k,…

A: Here we have given an option true followed with explanation.

Q: Following is the  table of pairwise Euclidean distances between  5 data points   a b c d e a 0…

A: An method called single linkage clustering divides data points into clusters. Each data point is…

Q: Draw a linne graph of the cluster center . How do you characterize each of the cluster

A: Clustering in ML is defined as identifying similarities between certain objects and making a group…

Q: python code

A: #1 Importing the librariesimport numpy as npimport matplotlib.pyplot as pltimport pandas as pd#2…

Disjoint set forest

The concept of the disjoint set forest was introduced by Bernard A. Galler and Michael J. Fischer in 1964. The disjoint set forest is a method of implementing disjoint sets quickly. In the disjoint-set forest, each tree member points only to its parent. The root of every tree includes its representative and its parent. The disjoint set forest is a special kind of forest that performs Union and Find operations in near-constant amortized time.