MACHINE LEARNING TECHNIQUES USED IN BIG DATA
The classical tools used in data analysis are not enough in order to benefit of all advantages of big data. The amount of information is too large for a complete investigation, and the possible connections and relations between data could be missed, because it is difficult or even impossible to veri...
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Veröffentlicht in: | Scientific Bulletin ("Mircea cel Bătrân" Naval Academy) 2016-01, Vol.19 (1), p.530-530 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | The classical tools used in data analysis are not enough in order to benefit of all advantages of big data. The amount of information is too large for a complete investigation, and the possible connections and relations between data could be missed, because it is difficult or even impossible to verify all assumption over the information. Machine learning is a great solution in order to find concealed correlations or relationships between data, because it runs at scale machine and works very well with large data sets. The more data we have, the more the machine learning algorithm is useful, because it "learns" from the existing data and applies the found rules on new entries. In this paper, we present some machine learning algorithms and techniques used in big data. |
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ISSN: | 1454-864X 2392-8956 |