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Books > Computing & IT > Applications of computing > Artificial intelligence
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Preference Learning (Hardcover, 2011 Ed.)
Loot Price: R4,694
Discovery Miles 46 940
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Preference Learning (Hardcover, 2011 Ed.)
Expected to ship within 10 - 15 working days
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The topic of preferences is a new branch of machine learning and
data mining, and it has attracted considerable attention in
artificial intelligence research in previous years. It involves
learning from observations that reveal information about the
preferences of an individual or a class of individuals.
Representing and processing knowledge in terms of preferences is
appealing as it allows one to specify desires in a declarative way,
to combine qualitative and quantitative modes of reasoning, and to
deal with inconsistencies and exceptions in a flexible manner. And,
generalizing beyond training data, models thus learned may be used
for preference prediction. This is the first book dedicated to this
topic, and the treatment is comprehensive. The editors first offer
a thorough introduction, including a systematic categorization
according to learning task and learning technique, along with a
unified notation. The first half of the book is organized into
parts on label ranking, instance ranking, and object ranking; while
the second half is organized into parts on applications of
preference learning in multiattribute domains, information
retrieval, and recommender systems. The book will be of interest to
researchers and practitioners in artificial intelligence, in
particular machine learning and data mining, and in fields such as
multicriteria decision-making and operations research.
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