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Which method is commonly used to select the right number of clusters? 1 pointThe elbow method. The ROC curve. The perfect Square MethodThe Sum of Square Method

Question

Which method is commonly used to select the right number of clusters? 1 pointThe elbow method. The ROC curve. The perfect Square MethodThe Sum of Square Method

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Solution

The method commonly used to select the right number of clusters is the Elbow Method.

Here are the steps to use the Elbow Method:

  1. Compute clustering algorithm (e.g., k-means) for different values of k. For instance, by varying k from 1 to 10 clusters.

  2. For each k, calculate the total within-cluster sum of square (wss).

  3. Plot the curve of wss according to the number of clusters k.

  4. The location of a bend (knee) in the plot is generally considered as an indicator of the appropriate number of clusters.

The ROC curve, Perfect Square Method, and Sum of Square Method are not typically used for determining the number of clusters.

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Question 3What is one of the most suitable ways to choose K when the number of clusters is unclear? 1 pointYou can start by choosing a random number of clusters. By evaluating Clustering performance such as Inertia and Distortion.By increasing the number of clusters calculating the square root. You can start by using a k nearest neighbor method.

The method / metric which is NOT useful to determine the optimal number of clusters in unsupervised clustering algorithms isReview LaterDendogramElbow methodScree plotNone of the above.

How is the optimal number of clusters determined in hierarchical clustering?*1 pointBy minimizing the between-cluster sum of squaresBy maximizing the within-cluster sum of squaresBy examining the dendrogram and selecting an appropriate cut-off pointBy using the elbow method on the resulting tree structure

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