Python Assignment | K-means Clustering
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Added on 2020-05-16
Python Assignment | K-means Clustering
Added on 2020-05-16
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Running head: ASSIGNMENTAssignmentName of the studentName of the universityAuthor’s note
1ASSIGNMENTTable of ContentsIntroduction:....................................................................................................................................2What is k-means clustering?........................................................................................................2K-means clustering in healthcare industries:...............................................................................3Discussion and Analysis:.................................................................................................................5k-means............................................................................................................................................5Logistic Regression.........................................................................................................................6
2ASSIGNMENTK-means ClusteringIntroduction:What is k-means clustering?K-means clustering helps to partition a given dataset through a certain number of clusters(assumed k clusters) for a fixed priori. Clustering is grouping of objects into different clusters.We define a total of k-clusters, one for each cluster. The centroids must be placed in such a waythat different outcomes come from different locations. The better way of k-means clustering is toplace the clusters as much far as it could be. We have to re-calculate k new centroids asbarycentres of the clusters resulting from the previous stage. The previous two steps are repeateduntil the centroids fluctuate. It generates a separate group of objects into groups from which themetric is to be minimised. The mathematical formulation for K-means algorithm is given as-The algorithm is significantly sensitive to the initial randomly chosen cluster centres. K-means clustering is a simple algorithm that has been adapted to many problem domains.
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