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Python Data Science Essentials
book

Python Data Science Essentials

by Alberto Boschetti
April 2015
Beginner content levelBeginner
258 pages
5h 48m
English
Packt Publishing
Content preview from Python Data Science Essentials

The detection and treatment of outliers

In data science, examples are at the core of learning from data processes. If unusual, inconsistent, or erroneous data is fed into the learning process, the resulting model may be unable to correctly generalize the accommodating of any new data. An unusually high value present in a variable may not only skew descriptive measures such as the mean and variance, but it may also distort how many algorithms learn from data, thus exposing them to unusual values and expecting unusual responses from them.

When a data point deviates markedly from the others in a sample, it is called an outlier. Any other expected observation is labeled as an inlier.

A point may be an outlier due to the following three general causes ...

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Publisher Resources

ISBN: 9781785280429Supplemental Content