A guidance-vector machine is usually a supervised learning design that divides the data into regions divided by a linear boundary. Here, the linear boundary divides the black circles within the white. Supervised learning algorithms make a mathematical model of a set of information which contains both equally the inputs and the desired outputs.[47]
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