Paperback. Condizione: Very Good. Ex-library paperback in very nice condition with the usual markings and attachments.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Condizione: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 320.
Da: Majestic Books, Hounslow, Regno Unito
EUR 26,48
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. pp. 320 Illus.
Da: ALLBOOKS1, Direk, SA, Australia
EUR 34,22
Quantità: 1 disponibili
Aggiungi al carrelloBrand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
Hard Cover. Condizione: Good. No Jacket. Ex-library with the usual features. The interior is clean and tight. Binding and cover are good. 180 pages. 265 pages. Ex-Library.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 27,90
Quantità: 4 disponibili
Aggiungi al carrelloCondizione: New. pp. 320.
Da: Versandbuchhandlung Kisch & Co., Fürstenberg OT Blumenow, Germania
EUR 3,95
Quantità: 1 disponibili
Aggiungi al carrelloGebundene Ausgabe. Condizione: Neu. Neu Neuware; teils original eingeschweisst; Rechnung mit MwSt.; new item, still sealed; -Data mining (DM) consists of extracting interesting knowledge from re- world, large & complex data sets; and is the core step of a broader process, called the knowledge discovery from databases (KDD) process. In addition to the DM step, which actually extracts knowledge from data, the KDD process includes several preprocessing (or data preparation) and post-processing (or knowledge refinement) steps. The goal of data preprocessing methods is to transform the data to facilitate the application of a (or several) given DM algorithm(s), whereas the goal of knowledge refinement methods is to validate and refine discovered knowledge. Ideally, discovered knowledge should be not only accurate, but also comprehensible and interesting to the user. The total process is highly computation intensive. The idea of automatically discovering knowledge from databases is a very attractive and challenging task, both for academia and for industry. Hence, there has been a growing interest in data mining in several AI-related areas, including evolutionary algorithms (EAs). The main motivation for applying EAs to KDD tasks is that they are robust and adaptive search methods, which perform a global search in the space of candidate solutions (for instance, rules or another form of knowledge representation). 288 pp. Englisch.
Da: Basi6 International, Irving, TX, U.S.A.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Da: Romtrade Corp., STERLING HEIGHTS, MI, U.S.A.
Condizione: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Da: SMASS Sellers, IRVING, TX, U.S.A.
Condizione: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. pp. 232.
Da: ALLBOOKS1, Direk, SA, Australia
EUR 46,99
Quantità: 5 disponibili
Aggiungi al carrelloBrand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
Da: Majestic Books, Hounslow, Regno Unito
EUR 39,97
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: New. pp. 232 Illus.
Da: Che & Chandler Versandbuchhandlung, Fürstenberg OT Blumenow, Germania
EUR 3,95
Quantità: 1 disponibili
Aggiungi al carrelloGebundene Ausgabe. Condizione: Neu. Neu Neuware; teils original eingeschweisst; Rechnung mit MwSt.; new item, still sealed; -Data mining (DM) consists of extracting interesting knowledge from re- world, large & complex data sets; and is the core step of a broader process, called the knowledge discovery from databases (KDD) process. In addition to the DM step, which actually extracts knowledge from data, the KDD process includes several preprocessing (or data preparation) and post-processing (or knowledge refinement) steps. The goal of data preprocessing methods is to transform the data to facilitate the application of a (or several) given DM algorithm(s), whereas the goal of knowledge refinement methods is to validate and refine discovered knowledge. Ideally, discovered knowledge should be not only accurate, but also comprehensible and interesting to the user. The total process is highly computation intensive. The idea of automatically discovering knowledge from databases is a very attractive and challenging task, both for academia and for industry. Hence, there has been a growing interest in data mining in several AI-related areas, including evolutionary algorithms (EAs). The main motivation for applying EAs to KDD tasks is that they are robust and adaptive search methods, which perform a global search in the space of candidate solutions (for instance, rules or another form of knowledge representation). 288 pp. Englisch.
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 41,66
Quantità: 1 disponibili
Aggiungi al carrelloCondizione: New. pp. 232.
Condizione: As New. Unread book in perfect condition.
Da: California Books, Miami, FL, U.S.A.
EUR 59,80
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Da: California Books, Miami, FL, U.S.A.
EUR 59,80
Quantità: Più di 20 disponibili
Aggiungi al carrelloCondizione: New.
Condizione: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Condizione: As New. Unread book in perfect condition.