A survey of machine learning algorithms for big data analytics
| Autor: | S. Athmaja, Vasantha Kavitha, M. Hanumanthappa |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
business.industry
Computer science Big data 020206 networking & telecommunications 02 engineering and technology Predictive analytics Machine learning computer.software_genre Support vector machine 0202 electrical engineering electronic engineering information engineering Task analysis 020201 artificial intelligence & image processing Algorithm design Social media Artificial intelligence business Literature survey Hidden Markov model computer Algorithm |
| Zdroj: | 2017 International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS). |
| DOI: | 10.1109/iciiecs.2017.8276028 |
| Popis: | Big data analytics is a booming research area in computer science and many other industries all over the world. It has gained great success in vast and varied application sectors. This includes social media, economy, finance, healthcare, agriculture, etc. Several intelligent machine learning techniques were designed and used to provide big data predictive analytics solutions. A literature survey of different machine learning techniques is provided in this paper. Also a study on commonly used machine learning algorithms for big data analytics is done and presented in this paper. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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