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Hands-On Automated Machine Learning
book

Hands-On Automated Machine Learning

by Sibanjan Das, Umit Mert Cakmak
April 2018
Beginner to intermediate content levelBeginner to intermediate
282 pages
6h 52m
English
Packt Publishing
Content preview from Hands-On Automated Machine Learning

Detecting and treating multivariate outliers

A multivariate outlier is a blend of extreme scores on at least two variables. Univariate outlier detection methods are suited well to dealing with single-dimension data, but when we get past single dimension, it becomes challenging to detect outliers using those methods. Multivariate outlier detection methods are also a form of anomaly detection methods. Techniques such as one class SVM, Local Outlier Factor (LOF), and IsolationForest are useful ways to detect multivariate outliers.

We describe multivariate outlier detection on the HR attrition dataset using the following IsolationForest code. We need to import the IsolationForest from the sklearn.ensemble package. Next, we load the data, transform ...

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Publisher Resources

ISBN: 9781788629898Supplemental Content