Ghosh Ashish (426 results)

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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.…

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.…

Soft cover. Condition: Very Good. 1st Edition. Springer, 2024. Collection of technical papers delivered at a conference at Charotar University of Science and Technology in Changa, India. Paperback, xix + 272 pages including author index. Illustrated with tables and figures. References at end of each article. This copy in very good condition overall. Clean, unmarked text. Firm binding. The only defect on this copy is a cut on the back hinge of the spine. Does not affect the durability of the spine. Book looks only lightly used. Nice copy. Book ships by Priority Mail to U.S. addresses at no extra charge to you. Just select standard shipping at checkout and I'll upgrade to Priority.…

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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. 349 pages. Ex-Library.

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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condition: As New. Unread book in perfect condition.

Condition: New. In English.

Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.