Intelligent Data Analysis : From Data Gathering to Data Comprehension /
"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 typic...
| Main Authors: | , , , |
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| Format: | text |
| Language: | eng |
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Hoboken, NJ, USA : Wiley,
2020
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| Subjects: |
| _version_ | 1826470260476215296 |
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| author | Gupta, Deepak, editor 636375 Bhattacharyya, Siddhartha, editor 563382 Khanna, Ashish, editor 636376 Sagar, Kalpna, editor 636377 |
| author_facet | Gupta, Deepak, editor 636375 Bhattacharyya, Siddhartha, editor 563382 Khanna, Ashish, editor 636376 Sagar, Kalpna, editor 636377 |
| author_sort | Gupta, Deepak, editor 636375 |
| collection | OCEAN |
| description | "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". |
| first_indexed | 2024-03-05T16:45:34Z |
| format | text |
| id | KOHA-OAI-TEST:593375 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| language | eng |
| last_indexed | 2024-03-05T16:45:34Z |
| publishDate | 2020 |
| publisher | Hoboken, NJ, USA : Wiley, |
| record_format | dspace |
| spelling | KOHA-OAI-TEST:5933752021-11-07T07:26:27ZIntelligent Data Analysis : From Data Gathering to Data Comprehension / Gupta, Deepak, editor 636375 Bhattacharyya, Siddhartha, editor 563382 Khanna, Ashish, editor 636376 Sagar, Kalpna, editor 636377 textHoboken, NJ, USA : Wiley,2020eng"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".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".Data miningComputational intelligenceURN:ISBN:9781119544456 |
| spellingShingle | Data mining Computational intelligence Gupta, Deepak, editor 636375 Bhattacharyya, Siddhartha, editor 563382 Khanna, Ashish, editor 636376 Sagar, Kalpna, editor 636377 Intelligent Data Analysis : From Data Gathering to Data Comprehension / |
| title | Intelligent Data Analysis : From Data Gathering to Data Comprehension / |
| title_full | Intelligent Data Analysis : From Data Gathering to Data Comprehension / |
| title_fullStr | Intelligent Data Analysis : From Data Gathering to Data Comprehension / |
| title_full_unstemmed | Intelligent Data Analysis : From Data Gathering to Data Comprehension / |
| title_short | Intelligent Data Analysis : From Data Gathering to Data Comprehension / |
| title_sort | intelligent data analysis from data gathering to data comprehension |
| topic | Data mining Computational intelligence |
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