How can we justify probability estimates are not to be completely trusted ?

Hey Swarntam, Thank you for your question! In the lesson, we make the difference between "predictions" and "prediction estimates". The former refers to the predictions themselves (a message is classified as a spam, or a ham). The latter refers to the certainty with which a prediction is made (a message is classified as spam with 70% certainty). One of the lessons that come later in the course ("The YouTube Dataset: Changing the priors") discusses why these probability estimates should not be entirely trusted. Kind regards, 365 Hristina

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Swarntam Saurav

Last answered:

18 Apr 2022

Posted on:

16 Apr 2022

Regarding con of classifier

in Machine Learning with Naïve Bayes / Motivation

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Hristina Hristova

Instructor

Posted on:

18 Apr 2022

Regarding con of classifier

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