| Autor: |
Jat, Dharm Singh, Dhaka, Poonam, Limbo, Anton |
| Zdroj: |
Journal of Statistics and Management Systems; July 2018, Vol. 21 Issue: 4 p639-645, 7p |
| Abstrakt: |
AbstractBig data is everywhere, and storage is affordable. The existing hardware and software are unable to analysis the vast amount of various types of data. Big data has become too complex and too dynamic to be able to process, store, analyze and manage with traditional data tools. Various statistical methods are important tools for big data analysis, but certain assumptions are required. So, a need emerges to explore an intelligent technique to analysis a large amount of data efficiently. One of the important approach used in machine learning is an artificial neural network (ANN) and is used to analysis the big data by using algorithms which allows learning, and the target value are based on data alone as compared to set of certain assumptions in statistical methods. Learning process can be simplified and automated by using iterative approach. This paper gives useful insight into the capabilities of Statistical Techniques and Artificial Neural Networks used in different types of applications. |
| Databáze: |
Supplemental Index |
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