Abstract
We give the first polynomial time prediction strategy for any PAC-learnable class C that probabilistically predicts the target with mistake probability
where t is the number of trials. The lower bound for the mistake probability is [HLW94] Ω(1/t) so our algorithm is almost optimal.
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© 2004 Springer-Verlag Berlin Heidelberg
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Bshouty, N.H. (2004). Polynomial Time Prediction Strategy with Almost Optimal Mistake Probability. In: Shawe-Taylor, J., Singer, Y. (eds) Learning Theory. COLT 2004. Lecture Notes in Computer Science(), vol 3120. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-27819-1_5
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DOI: https://doi.org/10.1007/978-3-540-27819-1_5
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22282-8
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