The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics.
The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics.
The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Vendeur : Indiana Book Company, Marion, IN, Etats-Unis
Etat : Acceptable. Book has liquid or water damage on pages. Ships same or next business day with delivery confirmation. Acceptable condition. Contains highlighting. Expedited shipping available. N° de réf. du vendeur 1000007517999-6800
Quantité disponible : 1 disponible(s)
Vendeur : World of Books (was SecondSale), Montgomery, IL, Etats-Unis
Hardback. Etat : Very Good. The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing. N° de réf. du vendeur CIN026208290XVG
Quantité disponible : 1 disponible(s)
Vendeur : World of Books (was SecondSale), Montgomery, IL, Etats-Unis
Hardback. Etat : Good. The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing. N° de réf. du vendeur 00099075634
Quantité disponible : 2 disponible(s)
Vendeur : ThriftBooks-Atlanta, AUSTELL, GA, Etats-Unis
Hardcover. Etat : Very Good. No Jacket. Missing dust jacket; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. N° de réf. du vendeur G026208290XI4N01
Quantité disponible : 1 disponible(s)
Vendeur : ThriftBooks-Dallas, Dallas, TX, Etats-Unis
Hardcover. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. N° de réf. du vendeur G026208290XI3N00
Quantité disponible : 1 disponible(s)
Vendeur : ThriftBooks-Dallas, Dallas, TX, Etats-Unis
Hardcover. Etat : Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less. N° de réf. du vendeur G026208290XI4N00
Quantité disponible : 1 disponible(s)
Vendeur : ThriftBooks-Atlanta, AUSTELL, GA, Etats-Unis
Hardcover. Etat : Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less. N° de réf. du vendeur G026208290XI3N00
Quantité disponible : 1 disponible(s)
Vendeur : Better World Books, Mishawaka, IN, Etats-Unis
Etat : Fine. Used book that is in almost brand-new condition. May contain a remainder mark. Better World Books: Buy Books. Do Good. N° de réf. du vendeur 5644136-6
Quantité disponible : 1 disponible(s)
Vendeur : Better World Books, Mishawaka, IN, Etats-Unis
Etat : Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. N° de réf. du vendeur 4326583-6
Quantité disponible : 1 disponible(s)
Vendeur : World of Books Inc, Montgomery, IL, Etats-Unis
Hardback. Etat : Very Good. The first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The growing interest in data mining is motivated by a common problem across disciplines: how does one store, access, model, and ultimately describe and understand very large data sets? Historically, different aspects of data mining have been addressed independently by different disciplines. This is the first truly interdisciplinary text on data mining, blending the contributions of information science, computer science, and statistics. The book consists of three sections. The first, foundations, provides a tutorial overview of the principles underlying data mining algorithms and their application. The presentation emphasizes intuition rather than rigor. The second section, data mining algorithms, shows how algorithms are constructed to solve specific problems in a principled manner. The algorithms covered include trees and rules for classification and regression, association rules, belief networks, classical statistical models, nonlinear models such as neural networks, and local "memory-based" models. The third section shows how all of the preceding analysis fits together when applied to real-world data mining problems. Topics include the role of metadata, how to handle missing data, and data preprocessing. N° de réf. du vendeur CIN026208290XVG
Quantité disponible : 1 disponible(s)