Data Clustering
In view of the considerable applications of data clustering techniques in various fields, such as engineering, artificial intelligence, machine learning, clinical medicine, biology, ecology, disease diagnosis, and business marketing, many data clustering algorithms and methods have been developed to...
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| Format: | eBook |
| Language: | English |
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IntechOpen
2022
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| Series: | Artificial Intelligence
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| Collection: | Directory of Open Access Books - Collection details see MPG.ReNa |
| Summary: | In view of the considerable applications of data clustering techniques in various fields, such as engineering, artificial intelligence, machine learning, clinical medicine, biology, ecology, disease diagnosis, and business marketing, many data clustering algorithms and methods have been developed to deal with complicated data. These techniques include supervised learning methods and unsupervised learning methods such as density-based clustering, K-means clustering, and K-nearest neighbor clustering. This book reviews recently developed data clustering techniques and algorithms and discusses the development of data clustering, including measures of similarity or dissimilarity for data clustering, data clustering algorithms, assessment of clustering algorithms, and data clustering methods recently developed for insurance, psychology, pattern recognition, and survey data. |
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| Item Description: | Creative Commons (cc), https://creativecommons.org/licenses/by/3.0/ |
| Physical Description: | 1 electronic resource (126 p.) |
| ISBN: | 9781839698873 intechopen.95124 9781839698897 9781839698880 |