January 2017
Beginner to intermediate
446 pages
8h 46m
English
Content preview from Artificial Intelligence with PythonBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Confusion matrix
A Confusion matrix is a figure or a table that is used to describe the performance of a classifier. It is usually extracted from a test dataset for which the ground truth is known. We compare each class with every other class and see how many samples are misclassified. During the construction of this table, we actually come across several key metrics that are very important in the field of machine learning. Let's consider a binary classification case where the output is either 0 or 1:
- True positives: These are the samples for which we predicted 1 as the output and the ground truth is 1 too.
- True negatives: These are the samples for which we predicted 0 as the output and the ground truth is 0 too.
- False positives: These are the samples ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.