A case study for an incremental classifier model in big data
| Autor: | S.S. Blessy Trencia Lincy, Suresh Kumar Nagarajan |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer Networks and Communications
business.industry Computer science Big data Predictive analytics Machine learning computer.software_genre Computer Science Applications Health care Computer Science (miscellaneous) Incremental build model Artificial intelligence business Classifier (UML) computer Software |
| Zdroj: | International Journal of Cloud Computing. 8:266 |
| ISSN: | 2043-9997 2043-9989 |
| DOI: | 10.1504/ijcc.2019.10025576 |
| Popis: | Big data is a term that implies enormous voluminous of data which cannot be handled by the existing traditional systems. With the evolving standards and technologies this volume has reached to a rate, such that even if provided with the huge amount of data it is a challenging task to obtain useful insights or knowledge out of it. Thus, this is a foremost and most important challenge for the researchers and scientists to transform the data or manipulate the data for analysis and processing them with the significant purpose of gaining insights out of it. In this paper, an incremental classifier model is applied for performing the classification with the evolving new instances of data and analysed as a case study. The experiment is carried out with the healthcare datasets to understand and analyse the suggested model and the proposed model is said to provide better performance that deals with large data. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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