Lecture 1 — March 27 , 2017
نویسنده
چکیده
We are given a training set S = {(xi, yi), 1 ≤ i ≤ m}, where each xi is an instance in some space X, e.g. a feature vector over Rd, and yi is a binary label (classification). For example, xi could be a set of features of an email message and y could be a label indicating whether it is spam or not. We assume that yi = f(xi) where f : X → {0, 1} is the correct labeling of the message, i.e., the ground truth. We also assume that each xi is drawn independently from some distribution D over the instance space.
منابع مشابه
Lectures On The Physical Approach To Donaldson And Seiberg-Witten Invariants Of Four-Manifolds
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تاریخ انتشار 2017