Machine Learning Essay

137814 Words Oct 12th, 2014 552 Pages
Foundations of Machine Learning

Adaptive Computation and Machine Learning Thomas Dietterich, Editor Christopher Bishop, David Heckerman, Michael Jordan, and Michael Kearns, Associate Editors A complete list of books published in The Adaptive Computations and Machine Learning series appears at the back of this book.

Foundations of Machine Learning
Mehryar Mohri, Afshin Rostamizadeh, and Ameet Talwalkar

The MIT Press Cambridge, Massachusetts London, England

c 2012 Massachusetts Institute of Technology All rights reserved. No part of this book may be reproduced in any form by any electronic or mechanical means (including photocopying, recording, or information storage and retrieval) without permission in writing from the
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2.5 2.6

PAC Learning Framework The PAC learning model . . . . . . . . . . . . . . . . . . Guarantees for finite hypothesis sets — consistent case . Guarantees for finite hypothesis sets — inconsistent case Generalities . . . . . . . . . . . . . . . . . . . . . . . . . 2.4.1 Deterministic versus stochastic scenarios . . . . . 2.4.2 Bayes error and noise . . . . . . . . . . . . . . . 2.4.3 Estimation and approximation errors . . . . . . . 2.4.4 Model selection . . . . . . . . . . . . . . . . . . . Chapter notes . . . . . . . . . . . . . . . . . . . . . . . . Exercises . . . . . . . . . . . . . . . . . . . . . . . . . . VC-Dimension . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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3 Rademacher Complexity and 3.1 Rademacher complexity . . 3.2 Growth function . . . . . . 3.3 VC-dimension . . . . . . . . 3.4 Lower bounds . . . . . . . . 3.5 Chapter notes . . . . . . . . 3.6 Exercises . . . . . . . . . .

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