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Question 2Which approach can be used to calculate dissimilarity of objects in clustering?1 pointCosine similarityMinkowski distanceEuclidian distanceAll of the above

Question

Question 2Which approach can be used to calculate dissimilarity of objects in clustering?1 pointCosine similarityMinkowski distanceEuclidian distanceAll of the above

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Solution

All of the above. In clustering, different approaches can be used to calculate the dissimilarity of objects. These include:

  1. Cosine similarity: This measures the cosine of the angle between two vectors. This value ranges from -1 to 1. The closer the cosine value to 1, the smaller the angle and the greater the match between vectors.

  2. Minkowski distance: This is a metric in a normed vector space which can be considered as a generalization of both the Euclidean distance and the Manhattan distance.

  3. Euclidean distance: This is the "ordinary" straight-line distance between two points in Euclidean space.

So, all of these

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