Suppose there are six cities in a state. The distance matrix between each pair of the cities is given below.What is the dendrogram generated by hierarchical clustering with single-linkage?AВDEFA60120185260300609021025832012018590140179200210132140179125E260258125135300320200132135Based on the resulting dendrogram, if we want to create 4 clusters, they areCluster NumberItems1

Given : The distance matrix is given. The task is to perform the hierarchical clustering on the…

Suppose there are six cities in a state. The distance matrix between each pair of the cities is given below What is the dendrogram generated by hierarchical clustering with single-linkage? F 300 320 A A 60 60 120 185 260 300 90 210 258 320 120 90 185 210 140 260 258 179 125 200 132 140 179 200 E 125 132 135 135 Based on the resulting dendrogram, if we want to create 4 clusters, they are Cluster Number 1 Items ~111

Suppose there are six cities in a state. The distance matrix between each pair of the cities is given below What is the dendrogram generated by hierarchical clustering with single-linkage? F 300 320 A A 60 60 120 185 260 300 90 210 258 320 120 90 185 210 140 260 258 179 125 200 132 140 179 200 E 125 132 135 135 Based on the resulting dendrogram, if we want to create 4 clusters, they are Cluster Number 1 Items ~111

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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please, I need to solve these, it contain python code and results.
Given an unlabeled dataset {x(1),...,x(m)}. The K-mean algorithm has been run with 40 different random initializations, and 40 different clusterings of the data have been Ex0 – µwl² to choose the best obtained. Describe how we should use m m clustering.
Urfan 21
Show how the mergesort algorithm executes on the string MATERIAL You should recall from lecture that we can use a graph to visualize the merge sort algorithm. At the very top of the graph, you have one node representing the original input list. At the very bottom, you have one node representing a sorted version of your input list. In the midle, you have nodes and edges representing the steps you take to execute merge sort. For this question, you are to execute the merge sort algorithm and show your work, with the provided string for input. You will consider each character in the input string as an element in an input list to merge sort. For example, the string "HELLO" would mean you input the list ["H", "E", "L", "L", "O"] into the merge sort algorithm. Fòr convenience, the pseudocode of the mergesort algorithm is shown below: MergeSort(array V, int p, int r) { if (p = r) then // do nothing else { // we have at least 2 items q = (p + r)/2 MergeSort(V, p, q) // sort V[p..a] MergeSort(V,…
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?
The source code should be in .ipynb format
Suppose that you need to group some data into clusters, and you run K-means 100 times, starting each time from a different random initialisation. You get 100 different clusterings of the data. Which one should you choose? Simply pick one at random. Choose the one that minimises the mean distance of points from the centroid of their allocated cluster. Label the clusters 1, 2, ..., Choose the clustering you get from the 100th run. k each time, and assign each point to the cluster it ends up in most often.
Solve this question involving sets.
Data Mining It is known that there are two point dimensions as shown in Table 2 below [Table attached below] By using the Hierarchical Clustering algorithm, please create a Cluster and a Dendogram and the steps (intermediary 2 matrix) in making the Dendogram using: Average Link. To measure distance please use Euclidean distance.
Q3. Compute the distance vector tables for each node, until they reach a settled state. Present your tables in the style used in the example and shown below, with each iteration appearing in a separate column. [15 marks] Iteration 1 Iteration 2 and so on... cost to Node Node А в с A A C A A 6 A 00 B 00 C 00 00 Node Node A B C D A C D B B A A 00 B 6 1 3 C D I and so on... 8 3. 8 8