02573nam 2200457 450 991055503510332120211005231017.01-119-54446-71-119-54444-01-119-54448-3(CKB)4100000010870942(MiAaPQ)EBC6177671(CaSebORM)9781119544456(OCoLC)1149370344(EXLCZ)99410000001087094220200818h20202020 uy 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierIntelligent data analysis from data gathering to data comprehension /edited by Deepak Gupta [and three others]Hoboken, NJ :Wiley,2020.©20201 online resource (xxix, 398 pages) illustrations1-119-54445-9 Includes bibliographical references and index."The new tool for analyses is ?Intelligent Data Analysis (IDA)?. IDA can be defined as the use of specialized statistical, pattern recognition, machine learning, data abstraction, and visualization tools for analysis of data and discovery of mechanisms that created the data. Such data are typically complex, meaning that they are characterized by many records, many variables, subtle interactions between variables, or a combination of all three. Engineering, computing sciences, database science, machine learning, and even artificial intelligence are bringing their powers to this newly born data analysis discipline. The main idea underlying the concept of Intelligent Data Analysis is extracting knowledge from a very large amount of data, with a very large amount of variables; data that represents very complex, non-linear, real-life problems. Moreover, IDA can help when starting from the raw data, coping with prediction tasks without knowing the theoretical description of the underlying process, classification tasks of new events based on past ones, or modeling the aforementioned unknown process. Classification, prediction, and modeling are the cornerstones that Intelligent Data Analysis can bring to us"--Provided by publisher.Data miningComputational intelligenceData mining.Computational intelligence.006.312Gupta DeepakMiAaPQMiAaPQMiAaPQBOOK9910555035103321Intelligent data analysis443686UNINA