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Established in 2016, the Data Institute at USF serves as the umbrella organization for data science research and programming at the University of San Francisco. We offer MS Data Science, BS Data Science and continuing education certificates.

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Choosing the Right Metric for Evaluating Machine Learning Models — Part 2

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Second part of the series focussing on classification metrics

In the first blog, we discussed some important metrics used in regression, their pros and cons, and use cases. This part will focus on commonly used metrics in classification, why should we prefer some over others with context.

Definitions

Let’s first understand the basic terminology used in classification problems before going through the pros and cons of each method. You can skip this section if you are already familiar with the terminology.

Source of Image: Wikipedia
  • Recall or Sensitivity or TPR (True Positive Rate): Number of items correctly identified as positive out of total true positives- TP/(TP+FN)
  • Specificity or TNR (True Negative Rate): Number of items correctly identified as negative out of total negatives- TN/(TN+FP)
  • Precision: Number of items correctly identified as positive out of total items identified…

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USF-Data Science
USF-Data Science

Published in USF-Data Science

Established in 2016, the Data Institute at USF serves as the umbrella organization for data science research and programming at the University of San Francisco. We offer MS Data Science, BS Data Science and continuing education certificates.

Alvira Swalin
Alvira Swalin

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