Overview of the Predictive Data Mining Techniques
DOI:
https://doi.org/10.26438/ijcse/v10i1.2836Keywords:
Extraction, Predictive Technique, Database, Classification, SVM, ClusteringAbstract
Data mining conciliations talented ways to expose secreted designs within huge volumes of data. These hidden designs can possibly be used to prediction forthcoming performance. The descriptive data mining tasks characterize the general properties of the data present in the database, while in contrast predictive data mining technique perform inference from the current data for making prediction. This overview briefly introduces these two most important techniques that perform data mining task as Predictive and Descriptive. Between this predictive and descriptive they consist of their own method as Classification, clustering, Data mining (knowledge discovery from data) may be viewed as the abstraction of interesting (non-trivial, implicit, previously unknown and potentially useful) patterns and models from observed data or a method used for analytical process designed to explore data. We know Data mining as knowledge discovery. Basically, Extraction or “MINING” means knowledge from large amount of data. the prediction analysis technique provided by the data mining the future scenarios regarding to the current information can be predicted. The prediction analysis is the combination of clustering and classification. In order to provide prediction analysis there are several techniques presented through many researchers. In this paper describes various techniques proposed by various authors are analysed to understand latest trends in the prediction analysis.
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