August 2018
Intermediate to advanced
522 pages
12h 45m
English
Content preview from Machine Learning Algorithms - Second Edition
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Introduction to statistical learning concepts
Imagine that you need to design a spam-filtering algorithm, starting from this initial (over-simplistic) classification based on two parameters:
| Parameter | Spam emails (X1) | Regular emails (X2) |
| p1 - Contains > 5 blacklisted words | 80 | 20 |
| p2 - Message length < 20 characters | 75 | 25 |
We have collected 200 email messages (X) (for simplicity, we consider p1 and p2 as mutually exclusive) and we need to find a couple of probabilistic hypotheses (expressed in terms of p1 and p2), to determine the following:
We also assume the conditional independence of both terms (it means that hp1 and hp2 contribute ...
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