An empirical comparative analysis of clustering algorithms for big data applications
Big data is a vaguely defined term that describes a dataset as either too large or too complex to analyze and get satisfactory results. Clustering algorithms are a possible solution to this problem of big data, where they can be categorized according to one or more of three clustering objectives. Th...
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| 格式: | text |
| 語言: | English |
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Animo Repository
2017
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| 在線閱讀: | https://animorepository.dlsu.edu.ph/etd_masteral/5395 |
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| 機構: | De La Salle University |
| 語言: | English |