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Lecture Notes in Machine Learning By Zdravko Markov

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Lecture Notes in Machine Learning By Zdravko Markov

Lecture Notes in Machine Learning By Zdravko Markov

This book contains the following topics: Concept learning, Languages for learning, Version space learning, Induction of Decision Trees, Covering strategies, Inductive Logic Programming, Bayesian approach and MDL, Unsupervised Learning,Paradigms, Learning semantic nets, Induction task, Relational languages, Language of logic programming, Search strategies in version space, Candidate Elimination Algorithm, Representing disjunctive concepts, Building a decision tree, Learning multiple concepts, Learning from noisy data, Basic idea, Basic idea, Searching the space of propositional hypotheses, Searching the space of relational hypotheses, ILP task, Ordering Horn clauses, Inverse Resolution, Predicate Invention, Extralogical restrictions, Illustrative examples, Basic strategies for solving the ILP problem, Bayesian induction, Occams razor, Evaluating propositional hypotheses, Evaluating relational hyporheses, Introduction, COBWEB, Introduction, Basic concepts of EBL, Example and Discussion

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s65 Pages
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