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Synopsis
In the area of artificial learners, not much research on the question of an appropriate description of artificial learner’s (empirical) performance has been conducted. The optimal solution of describing a learning problem would be a functional dependency between the data, the learning algorithm’s internal specifics and its performance. Unfortunately, a general, restrictions-free theory on performance of arbitrary artificial learners has not been developed yet. This work addresses the problem of measuring and observing the artificial learners, specifically the decision trees produced by the C4.5 algorithm. A procedure for measuring the learning progress, called adaptive incremental k-fold cross-validation is presented, together with other tools and techniques needed to observe artificial learners on their course of learning. Early observations can be used to forecast the future performance of a learner based on a small training sample.
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About the Author
Dr. Boštjan Brumen has obtained his PhD in Informatics in 2004. Since then he has worked in in several data-related international projects. His research interests include artificial intelligence, machine learning and learning progress. He is the author of several articles published in top journals, including Journal of Medical Internet Research.
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Assessment of Classification Algorithms in Artificial Intelligence
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the area of artificial learners, not much research on the question of an appropriate description of artificial learner's (empirical) performance has been conducted. The optimal solution of describing a learning problem would be a functional dependency between the data, the learning algorithm's internal specifics and its performance. Unfortunately, a general, restrictions-free theory on performance of arbitrary artificial learners has not been developed yet. This work addresses the problem of measuring and observing the artificial learners, specifically the decision trees produced by the C4.5 algorithm. A procedure for measuring the learning progress, called adaptive incremental k-fold cross-validation is presented, together with other tools and techniques needed to observe artificial learners on their course of learning. Early observations can be used to forecast the future performance of a learner based on a small training sample. 172 pp. Englisch. Seller Inventory # 9783659562518
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Assessment of Classification Algorithms in Artificial Intelligence
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Assessment of Classification Algorithms in Artificial Intelligence
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Taschenbuch. Condition: Neu. Assessment of Classification Algorithms in Artificial Intelligence | Bo¿tjan Brumen | Taschenbuch | 172 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659562518 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Seller Inventory # 105184314
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Assessment of Classification Algorithms in Artificial Intelligence
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In the area of artificial learners, not much research on the question of an appropriate description of artificial learner's (empirical) performance has been conducted. The optimal solution of describing a learning problem would be a functional dependency between the data, the learning algorithm's internal specifics and its performance. Unfortunately, a general, restrictions-free theory on performance of arbitrary artificial learners has not been developed yet. This work addresses the problem of measuring and observing the artificial learners, specifically the decision trees produced by the C4.5 algorithm. A procedure for measuring the learning progress, called adaptive incremental k-fold cross-validation is presented, together with other tools and techniques needed to observe artificial learners on their course of learning. Early observations can be used to forecast the future performance of a learner based on a small training sample.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 172 pp. Englisch. Seller Inventory # 9783659562518
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Assessment of Classification Algorithms in Artificial Intelligence
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In the area of artificial learners, not much research on the question of an appropriate description of artificial learner's (empirical) performance has been conducted. The optimal solution of describing a learning problem would be a functional dependency between the data, the learning algorithm's internal specifics and its performance. Unfortunately, a general, restrictions-free theory on performance of arbitrary artificial learners has not been developed yet. This work addresses the problem of measuring and observing the artificial learners, specifically the decision trees produced by the C4.5 algorithm. A procedure for measuring the learning progress, called adaptive incremental k-fold cross-validation is presented, together with other tools and techniques needed to observe artificial learners on their course of learning. Early observations can be used to forecast the future performance of a learner based on a small training sample. Seller Inventory # 9783659562518
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