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Evolutionary Computation Data Mining (142 results)
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Condition: New. pp. 320.
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Paperback. Condition: Very Good. We are unable to ship to Canada at this time.Ex-library paperback in very nice condition with the usual markings and attachments.
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Condition: New. pp. 320 Illus.
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Condition: New. pp. 320.
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Condition: 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.
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Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Condition: 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.
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Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
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Hard Cover. Condition: 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.
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Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
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Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
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Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing)
Book 13 of 183: Studies in Fuzziness and Soft ComputingSeller: Versandbuchhandlung Kisch & Co., Fürstenberg OT Blumenow, Germany
Seller rating 4 out of 5 stars
Gebundene Ausgabe. Condition: 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.
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Condition: New. pp. 232.
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International EditionCondition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 7-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Condition: New. pp. 232 Illus.
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Evolutionary Computation in Data Mining (Studies in Fuzziness and Soft Computing)
Book 13 of 183: Studies in Fuzziness and Soft ComputingSeller: Che & Chandler Versandbuchhandlung, Fürstenberg OT Blumenow, Germany
Seller rating 5 out of 5 stars
Gebundene Ausgabe. Condition: 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.
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Condition: New. pp. 232.
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Condition: As New. Unread book in perfect condition.
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Condition: As New. Unread book in perfect condition.
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Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics: 11th European Conference, EvoBIO 2013, Vienna, Austria, April 3-5, 2013, ... Computer Science and General Issues)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
US$ 61.37
US$ 15.65 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
