Introductory textbook presenting relational methods in machine learning.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
M. E. Mueller is a Professor of Computer Science at the Bonn-Rhein-Sieg University of Applied Sciences.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
EUR 14,87 expédition depuis Royaume-Uni vers Etats-Unis
Destinations, frais et délaisEUR 3,88 expédition vers Etats-Unis
Destinations, frais et délaisVendeur : Anybook.com, Lincoln, Royaume-Uni
Etat : Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,600grams, ISBN:9780521122047. N° de réf. du vendeur 5783205
Quantité disponible : 1 disponible(s)
Vendeur : Labyrinth Books, Princeton, NJ, Etats-Unis
Etat : New. N° de réf. du vendeur 144802
Quantité disponible : 5 disponible(s)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Etat : New. N° de réf. du vendeur ABLIING23Feb2215580244128
Quantité disponible : Plus de 20 disponibles
Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9780521122047
Quantité disponible : Plus de 20 disponibles
Vendeur : Grand Eagle Retail, Bensenville, IL, Etats-Unis
Paperback. Etat : new. Paperback. What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual properties of different approaches. What is knowledge and how is it represented? This introductory textbook presents relational methods in machine learning. Its clear and precise presentation is ideal for undergraduate computer science students and it will also interest those who study artificial intelligence or machine learning at the graduate level. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9780521122047
Quantité disponible : 1 disponible(s)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In. N° de réf. du vendeur ria9780521122047_new
Quantité disponible : Plus de 20 disponibles
Vendeur : THE SAINT BOOKSTORE, Southport, Royaume-Uni
Paperback / softback. Etat : New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 550. N° de réf. du vendeur C9780521122047
Quantité disponible : Plus de 20 disponibles
Vendeur : Chiron Media, Wallingford, Royaume-Uni
Paperback. Etat : New. N° de réf. du vendeur 6666-IUK-9780521122047
Quantité disponible : 10 disponible(s)
Vendeur : Revaluation Books, Exeter, Royaume-Uni
Paperback. Etat : Brand New. 1st edition. 288 pages. 9.61x6.77x0.63 inches. In Stock. This item is printed on demand. N° de réf. du vendeur __052112204X
Quantité disponible : 1 disponible(s)
Vendeur : CitiRetail, Stevenage, Royaume-Uni
Paperback. Etat : new. Paperback. What is knowledge and how is it represented? This book focuses on the idea of formalising knowledge as relations, interpreting knowledge represented in databases or logic programs as relational data and discovering new knowledge by identifying hidden and defining new relations. After a brief introduction to representational issues, the author develops a relational language for abstract machine learning problems. He then uses this language to discuss traditional methods such as clustering and decision tree induction, before moving onto two previously underestimated topics that are just coming to the fore: rough set data analysis and inductive logic programming. Its clear and precise presentation is ideal for undergraduate computer science students. The book will also interest those who study artificial intelligence or machine learning at the graduate level. Exercises are provided and each concept is introduced using the same example domain, making it easier to compare the individual properties of different approaches. What is knowledge and how is it represented? This introductory textbook presents relational methods in machine learning. Its clear and precise presentation is ideal for undergraduate computer science students and it will also interest those who study artificial intelligence or machine learning at the graduate level. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N° de réf. du vendeur 9780521122047
Quantité disponible : 1 disponible(s)