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Can you suggest some ways in which the performance of a clustering algorithm can be measured when the labels are given?

Machine Learning Engineer

Google

Amadeus

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Virta

MathWorks

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Answers

Anonymous

7 months ago
3.4Strong
We can compare the predicted labels with the actually labels. If we are only interested in a single cluster this becomes a binary classification problem. If we are interested in all clusters, this becomes a multi class prediction problem. In either case we can calculate accuracy, precision, recall and other metrics
  • Can you suggest some ways in which the performance of a clustering algorithm can be measured when the labels are given?
  • If you are working on a clustering task where the labels are already known, how would you determine the effectiveness of the model?
  • What techniques might you use to evaluate a clustering model's performance if label information is present?
  • As the labels are known in your clustering exercise, what approaches will you take to evaluate the model's performance?
  • Considering that you already have labelled data for your clustering project, what are some of the methods that you can use to evaluate model performance?
  • How would you measure the effectiveness of a clustering model if the labels are available beforehand?
  • What methodologies do you suggest for assessing the accuracy of a clustering algorithm when the labels are known in advance?
  • Given that you have labels for your clustering problem, what steps would you take to assess the performance of the model?
  • Please describe what techniques you would use to determine the accuracy and effectiveness of a clustering model while working with pre-existing labels.
  • If the labels are known in a clustering project, how would you evaluate the performance of the model?
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Interview question asked to Machine Learning Engineers interviewing at AT&T, Amadeus, IBM and others: Can you suggest some ways in which the performance of a clustering algorithm can be measured when the labels are given?.