Which of the following distance/similarity measure is invariant to scaling and translation?a.Correlationb.Cosinec.Euclideand.Manhattan

36.Which of the following combination is incorrect?  A. Continuous – euclidean distance  B. Continuous – correlation similarity  C. Binary – manhattan distance  D. You should choose a distance/similarity that makes sense for your problem.

Which of the following statements on proximity measures is FALSE?AIf the Euclidean distance of 2 vectors is zero, the cosine similarity is also always zeroBIf the cosine similarity of 2 vectors is zero, the Euclidean distance is also always zeroCIf the Manhattan distance of 2 vectors is zero, the cosine similarity is also always zeroDAll of the choices

Which of the following distance metrics is commonly used in hierarchical clustering?Cosine similarityEuclidean distanceJaccard indexHamming distance

Cosine similarity is a metric used to measure the similarity between two non-zero vectors in a multi-dimensional space. It's widely used in various fields, including natural language processing, information retrieval, recommendation systems, and more. Cosine similarity is particularly popular in text analysis and document retrieval tasks.

In hierarchical clustering, the distance between clusters is typically measured using the ______________ criterion.Select one:a.Cosine similarityb.Manhattan distancec.Linkage criteriond.Euclidean distance