30 lines
633 B
Matlab
30 lines
633 B
Matlab
function scores = kp_predict(alphas, b, d, X, Y, tst_data)
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% alphas, b: sample weights and bias term for classification
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% d: degree of polynomial kernel <x,y>^d
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% X,Y: training data and label
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% tst_data: test data for prediction
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% scores: the perdiction scores.
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N = size(X,1);
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%TO DO: calculate the predictions
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[tst_size, ~] = size(tst_data);
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scores = zeros(tst_size, 1);
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for t = 1 : tst_size
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xt = tst_data(t, :);
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sum = 0;
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for i = 1 : N
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ai = alphas(i);
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yi = Y(i);
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xi = X(i, :);
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sum = sum + ai * yi * dot(xi, xt) ^ d;
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end
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sum = sum + b;
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scores(t) = sign(sum);
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end
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%******************************** |