December 2018
Intermediate to advanced
318 pages
8h 28m
English
Content preview from Hands-On Machine Learning for Cybersecurity
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Random oversampling
This is the exactly opposite process of under-sampling; here, elements of the minority class are randomly added until the ratio between the majority and minority classes is close enough. The oversampling is a good method overall for addressing the issues that under-sampling faces. However, the major issue of oversampling is overfitting, where the results are too tailored to the input data.
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