April 2019
Beginner to intermediate
252 pages
4h 40m
English
Support Vector Machines (SVMs) models were built to predict categorical and continuous outcomes and are especially good when you have many predictors. They were developed for difficult predicting situations where linear models were unable to separate the categories of the outcome field. They too work like black boxes, hiding their complex work in predicting results. Let's get an insight into how SVMs work.
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