FEM 2063 Data Analytics Chapter 8: Clustering Quiz
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Questions and Answers

What is the main goal of clustering?

  • To predict the outcome of a target variable
  • To classify data into predefined categories
  • To find distinct groups in a data set that are similar within each group (correct)
  • To calculate the mean of the dataset
  • Which type of learning are clustering methods categorized under?

  • Reinforcement learning
  • Supervised learning
  • Semi-supervised learning
  • Unsupervised learning (correct)
  • How are points within the same cluster expected to be?

  • No similarity required
  • Randomly assigned
  • As similar as possible (correct)
  • As different as possible
  • What is one common application of clustering in business?

    <p>Market Segmentation</p> Signup and view all the answers

    Which clustering technique involves finding centroids and updating the cluster assignments iteratively?

    <p>K-Means Clustering</p> Signup and view all the answers

    In clustering, what does it mean to say points in the same group are 'quite similar'?

    <p>Have minimal differences based on a defined similarity measure</p> Signup and view all the answers

    What is the key property of the clusters in K-Means Clustering?

    <p>The clusters are non-overlapping</p> Signup and view all the answers

    What is the objective of K-Means Clustering?

    <p>To minimize the within-cluster variation</p> Signup and view all the answers

    How is the within-cluster variation W(Ck) defined in K-Means Clustering?

    <p>As the sum of squared Euclidean distances between observations in the cluster</p> Signup and view all the answers

    What is the optimization problem that defines K-Means Clustering?

    <p>Minimize the sum of squared Euclidean distances between observations and their assigned cluster centroids</p> Signup and view all the answers

    What is one of the weaknesses of K-Means Clustering mentioned in the text?

    <p>It requires the user to specify the number of clusters (K) in advance</p> Signup and view all the answers

    What is one of the strengths of K-Means Clustering mentioned in the text?

    <p>It is a simple iterative method</p> Signup and view all the answers

    What is the main objective of K-means clustering?

    <p>Classifying observations based on features</p> Signup and view all the answers

    In K-means clustering, what is done at the end of the 1st iteration?

    <p>Determining which points belong to which clusters</p> Signup and view all the answers

    What criterion is used to determine when to stop the K-means clustering process?

    <p>Minimum movement of cluster centers</p> Signup and view all the answers

    Which property must sets 𝐶1, ..., 𝐶𝑘 satisfy in K-means clustering?

    <p>Disjointness: no observation can belong to multiple clusters</p> Signup and view all the answers

    What is the purpose of finding the Euclidean distance between cluster center and each point in K-means clustering?

    <p>To update the cluster centers iteratively</p> Signup and view all the answers

    Which step in K-means clustering involves recalculating the cluster centers based on the points assigned to each cluster?

    <p>Finding the new cluster centers</p> Signup and view all the answers

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