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Consider the training set shown below, where "x" denotes positive examples (y=1) and "o" denotes negative examples (y=0). Suppose you train an SVM (which will predict 1 when Bo+ e1 Xi-82 X2 2 0). What values might the SVM give for 80, 81, 6z for the given decision boundary ? show calculations x2 ... 4 X X х1 2.

Consider the training set shown below, where "x" denotes positive examples (y=1) and "o" denotes negative examples (y=0). Suppose you train an SVM (which will predict 1 when Bo+ e1 Xi-82 X2 2 0). What values might the SVM give for 80, 81, 6z for the given decision boundary ? show calculations x2 ... 4 X X х1 2.

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Consider the training set shown below, where "x" denotes positive examples (y=1) and "o" denotes negative examples (y=0). Suppose you train an SVM (which will predict 1 when Bo+ e1 Xi-82 X2 2 0). What values might the SVM give for 80, 81, 6z for the given decision boundary ? show calculations x2 ... 4 X X х1 2.
Transcribed Image Text:Consider the training set shown below, where "x" denotes positive examples (y=1) and "o" denotes negative examples (y=0). Suppose you train an SVM (which will predict 1 when Bo+ e1 Xi-82 X2 2 0). What values might the SVM give for 80, 81, 6z for the given decision boundary ? show calculations x2 ... 4 X X х1 2.
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