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support vector machines have a lot of terminology associated with them brace yourself hello Iamp;#39;m Josh stormer and welcome to stat quest today weamp;#39;re going to talk about support vector machines and theyamp;#39;re gonna be clearly explained note this stack quest assumes that you are already familiar with the trade-off that plagues all of machine learning the bias-variance tradeoff you should also be familiar with cross-validation if not check out the quests the links are in the description below letamp;#39;s start by imagining we measured the mass of a bunch of mice the red dots represent mice that are not obese and the green dots represent mice that are obese based on these observations we can pick a threshold and when we get a new observation that has less mass than the threshold we can classify it as not obese and when we get a new observation with more mass than the threshold we can classify it as obese however what if we get a new observation here because this observ
