Data Interview Question

Minimizing Clustering Errors

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  • Objective: Partition n numbers into k groups to minimize the sum of errors within each group.
  • Error Metric: Typically involves minimizing the within-cluster sum of squares (WCSS), which is the sum of squared distances between each data point and the centroid of its assigned cluster.
  • Constraints: The number of clusters k is predetermined, and the data points are numerical values.
  • Assumptions:
    • Data is numerical and can be represented in a Euclidean space.
    • The number of clusters k is known beforehand.
    • Clusters are convex and isotropic, which means they have a spherical shape in the data space.