By Miroslav Kubat
This textbook offers basic computer studying strategies in a simple to appreciate demeanour by means of supplying sensible suggestion, utilizing hassle-free examples, and providing attractive discussions of suitable functions. the most subject matters comprise Bayesian classifiers, nearest-neighbor classifiers, linear and polynomial classifiers, choice timber, neural networks, and help vector machines. Later chapters express easy methods to mix those basic instruments in terms of “boosting,” the best way to make the most them in additional complex domain names, and the way to house different complicated useful matters. One bankruptcy is devoted to the preferred genetic algorithms.
This revised variation includes 3 fullyyt new chapters on severe subject matters concerning the pragmatic software of computer studying in undefined. The chapters research multi-label domain names, unsupervised studying and its use in deep studying, and logical methods to induction. quite a few chapters were improved, and the presentation of the fabric has been better. The publication includes many new routines, quite a few solved examples, thought-provoking experiments, and machine assignments for autonomous work.
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Extra info for An Introduction to Machine Learning
An Introduction to Machine Learning by Miroslav Kubat