Titlebook: Machine Learning and Its Applications; Advanced Lectures Georgios Paliouras,Vangelis Karkaletsis,Constantin Textbook 2001 Springer-Verlag B

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0302-9743 , commerce, and industry. Data mining is perhaps the most widely known demonstration of this migration, complemented by less publicized applications of machine learning like adaptive systems in industry, financial prediction, medical diagnosis and the construction of user profiles for Web browsers..

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Genetic Algorithms in Machine Learningned solely by the properties of the problems. A random process helps to guide the search. Genetic algorithms are used in artificial intelligence like other search algorithms are used in artificial intelligence — to search a space of potential solutions to find one which solves the problem.

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Unsupervised Learning of Probabilistic Concept Hierarchiesy learn names for them, and scientists regularly discover patterns without any clear supervision from an outside source. Even the availability of class labels in public data sets can be misleading; many such domains are medical in nature, and medical researchers first had to discover a disease before they could diagnose it for particular patients.

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Case-Based Reasoningthe CBR components, such as indexing/retrieval/selection, memory organization, adaptation/evaluation, forgetting, and integration with other techniques. Finally, we discuss the added value of incorporating fuzzy techniques in CBR and briefly describe some representative Fuzzy-CBR systems.

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