June 2020
Intermediate to advanced
382 pages
11h 39m
English
Content preview from 40 Algorithms Every Programmer Should Know
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Confusion matrix
A confusion matrix is used to summarize the results of the evaluation of a classifier. The confusion matrix for a binary classifier looks as follows:
If the label of the classifier we are training has two levels, it is called a binary classifier. The first critical use case of supervised machine learning—specifically, a binary classifier—was during the First World War to differentiate between an aircraft and flying birds.
The classification can be divided into the following four categories:
True positives (TP): The positive classifications that were correctly classified
True Negatives (TN): The negative classifications
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