Browsing by Author "Mukherjee, Sumita"

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    Integrating Application with Algorithms of Association Rule used in Descriptive Data Modelling, through which Data Mining can be Implemented for Future Prediction
    (International Journal of Applied Engineering Research, 2018) Musau, Felix; Gupta, Prinima; Mukherjee, Sumita
    Data mining is a most appropriate discipline which clubs up statistics, database technology, knowledge discovery, pattern recognition, machine learning, business, natural disaster and other areas. It interferes and integrates in such a manner which is the most suitable for identifying a valid, logical and understandable pattern to influence the expansion and productivity of an operation, profitability, increase in sales and retail measurements, prediction of natural disaster, less faulty production, desired human resources. What is Data? A fact and figure what is knowledge? Data collected in such a manner that we know about the data. What is information? Flowing of proper data through communication. What is Statistics? Based on data, knowledge and information is a decision maker and systematic evidence based on intellectual science. This Paper will give an idea of the importance and significance of data mining in a manner that the knowledge acquired by learning descriptive data mining can be easily applied on predictive action. It also targets to fragment the fascinating correlations, the maximum used arrangements and alliances among the products in product range in the proceeding database. Once the understanding and concept on descriptive data modelling is clear the application on predictive model becomes easy, productive and more appropriate to take decision positively to footprint the accomplishment of the overall system.