Suppose you have run k-means using k=2 and k=5. You find that the cost function J is much higher for k=5 than k=2. What can you conclude? • The ideal number of clusters is k=2. O* In the run with k=2, k-means got lucky. You should try re-running k-means with k=2 and different random initializations until it performs no better than with k=5. o« In the run with k=5, k-means got stuck in a bad local minimum. You should try re-running k-means with multiple random initializations. Od. This is mathematically impossible. There must be a bug in the code.

Suppose you have run k-means using k=2 and k=5. You find that the cost function J is much higher for k=5 than k=2. What can you conclude? • The ideal number of clusters is k=2. O* In the run with k=2, k-means got lucky. You should try re-running k-means with k=2 and different random initializations until it performs no better than with k=5. o« In the run with k=5, k-means got stuck in a bad local minimum. You should try re-running k-means with multiple random initializations. Od. This is mathematically impossible. There must be a bug in the code.

Database System Concepts

7th Edition

ISBN:9780078022159

Author:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Publisher:Abraham Silberschatz Professor, Henry F. Korth, S. Sudarshan

Chapter1: Introduction

Section: Chapter Questions

Problem 1PE

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Question

Suppose you have run k-means using k=2 and k=5. You find that the cost function J is
much higher for k=5 than k=2. What can you conclude?
The ideal number of clusters is k=2.
O b In the run with k=2, k-means got lucky. You should try re-running k-means with k=2
and different random initializations until it performs no better than with k=5.
O. In the run with k=5, k-means got stuck in a bad local minimum. You should try
re-running k-means with multiple random initializations.
Od.
This is mathematically impossible. There must be a bug in the code.

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