Assume in K-Means algorithm, we assign three centers c1, c2 and c3 for three clusters. We usually stop the clustering process when no changes in the centers happen, but if we do not reach to this stage, what do you propose to stop? Use the editor to format your answer
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- 2) Given a Clustering task, how you can evaluate the performance on the test set and how wewould know if the clusters are correct. Explain any three possible solutions.Compose a Python program to find the convergence of two given clusters utilizing Lambda.Unique exhibits:[1, 2, 3, 5, 7, 8, 9, 10][1, 2, 4, 8, 9]Convergence of the said clusters: [1, 2, 8, 9].After learning about the k-means clustering algorithm in the big data course, some of your classmates tell you that they are not very enthusiastic about using it. The main reason they provide is that, when applied to the same dataset, the algorithm seems to be giving different clusters every times it is run. What should you say to them? You should explain to them that they are interpreting the computer output incorrectly. Even though K-means seems to give different clusters every time it is run on the same dataset, if they look more closely at those clusters, they will notice that they are really the same clusters, but with different labels. You should explain to them that they are using the computer functions incorrectly. The K-means algorithm always results in the same clusters. You should explain to them that they should run the k-means algorithm several times and then pick up the clusters with the smallest objective function (all while warning them…
- 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,…Correct answer will be upvoted else Multiple Downvoted. Don't submit random answer. Computer science. You can utilize the accompanying activity however many occasions as you like: select any integer 1≤k≤n and do one of two things: decrement by one k of the primary components of the cluster. decrement by one k of the last components of the exhibit. For instance, in the event that n=5 and a=[3,2,2,1,4], you can apply one of the accompanying activities to it (not all potential choices are recorded underneath): decrement from the initial two components of the exhibit. After this activity a=[2,1,2,1,4]; decrement from the last three components of the exhibit. After this activity a=[3,2,1,0,3]; decrement from the initial five components of the cluster. After this activity a=[2,1,1,0,3]; Decide whether it is feasible to make every one of the components of the cluster equivalent to zero by applying a specific number of tasks. Input The principal line contains one…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?
- implement other algorithms of data mining (e.g. k-nearest neighbors (KNN) for classification, AGNES method for cluster analysis), and compare with the close pattern and maximal pattern algorithms in your report.Instead of using an array to store pointers to linked lists, you would like to explore using an AVL tree that you have pre-populated with a node for each address in the hash table. Therefore, the number of nodes n in the AVL tree corresponds to the size of the hash table. How would using an AVL tree to store the pointers to the linked lists affect the running time of insertions, deletions, and finds in the hash table? Your answer must include a justification that describes the running time in terms of the hash table size. You must use big-Oh notation. For clarification, here is an example of a hash table (with table size = 6) using Separate Chaining. "Prima" "Butera" - "Smith" 1 2 "Presley" |/ 3 4 "Sinatra" "Martin" "Davis" 5 Here is an example of the same items stored in the new AVL Tree – Separate Chaining approach you must explore. 3 2 "Sinatra" "Martin" "Davis" "Presley" / "Prima" "Butera" "Smith" /Subject: Machine Learning Apply single-link and complete-link hierarchical clustering method to construct two different dendrograms. Using the two dendrograms find the number of clusters at distance 8 [Hint: cut the dendrogram at distance 8].
- In hierarchical clustering, observations start in their own cluster then observations are iteratively combined based on a specific dissimilarity measurement. Consider the following statements about the agglomerative methods for measuring dissimilarity between observations. Indicate which of the following statements are TRUE in regards to single linkage. (Hint see page 222 of your text) • Statement A. Single linkage (nearest neighbor) will consider merging two clusters when an observation in a cluster is close to at least one observation from the other cluster. [Select) • Statement B. Complete linkage (farthest neighbor) merges two clusters if the distance between observations that are most different are relatively close to each other. ISelect] • Statement C. With only two variables, complete linkage may result in long elongated clusters instead of compact circular clusters. I Select ] • Statement D. Clusters produced by single linkage have approximately equal diameters. [ Select […write Algorithm to SiftInput: a (not necessarily complete) table T for the group G;an element g ~ G;Output: a modified table T such that g ~ closure (T) ;Correct answer will be upvoted else downvoted. Computer science. Officially, you should find a cluster b1,b2,… ,bn, to such an extent that the arrangements of components of exhibits an and b are equivalent (it is identical to cluster b can be found as a cluster a with some reordering of its components) and ∑i=1nMEX(b1,b2,… ,bi) is expanded. MEX of a bunch of nonnegative integers is the negligible nonnegative integer to such an extent that it isn't in the set. For instance, MEX({1,2,3})=0, MEX({0,1,2,4,5})=3. Input The primary line contains a solitary integer t (1≤t≤100) — the number of experiments. The primary line of each experiment contains a solitary integer n (1≤n≤100). The second line of each experiment contains n integers a1,a2,… ,an (0≤ai≤100). Output For each experiment print an exhibit b1,b2,… ,bn — the ideal reordering of a1,a2,… ,an, so the amount of MEX on its prefixes is amplified. If there exist different ideal answers you can view as any