Consider a variant of the Winnow algorithm which sets wit+1+3w, when it makes a mistake on positive examples (when Yt = 1 and ŷt = 0) and sets wit+1+wi,t/4 when it makes a mistake on negative examples (when y₁ = 0 and ŷ₁ = 1). Follow the same analysis steps as we did in the class to derive an upper bound for the number of mistakes of the algorithm for learning monotone disjunctions.
Consider a variant of the Winnow algorithm which sets wit+1+3w, when it makes a mistake on positive examples (when Yt = 1 and ŷt = 0) and sets wit+1+wi,t/4 when it makes a mistake on negative examples (when y₁ = 0 and ŷ₁ = 1). Follow the same analysis steps as we did in the class to derive an upper bound for the number of mistakes of the algorithm for learning monotone disjunctions.
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Transcribed Image Text:Consider a variant of the Winnow algorithm which sets wit+1+3w, when it makes a mistake on positive examples (when
Yt = 1 and ŷt = 0) and sets wit+1+wi,t/4 when it makes a mistake on negative examples (when y₁ = 0 and ŷ₁ = 1).
Follow the same analysis steps as we did in the class to derive an upper bound for the number of mistakes of the algorithm
for learning monotone disjunctions.
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