Review of Predictive Analytic Modeling Techniques

Razeef Mohammad, Muheet Ahmed Butt, Majid Zaman

Abstract Data Mining techniques and tools has become important and useful for extracting and manipulating historical data and for establishing relationships and patterns among data in order to generate useful information for decision-making. The proposed research work presents various predictive analytic techniques that are useful for effective decision making and prediction. These techniques are used to improve prediction and decision making in many fields such as: weather prediction, marketing, business, medicine etc. In this work we have discussed four main predictive analytic techniques viz., Classification, Regression, Clustering and Association Analysis and their applications in various domains. Keywords: Data Mining, Predictive Analytics, Regression, Classification, Clustering and Association Analysis.

Title:	Review of Predictive Analytic Modeling Techniques
Author Name:	Razeef Mohammad, Muheet Ahmed Butt, Majid Zaman
Abstract:	Abstract Data Mining techniques and tools has become important and useful for extracting and manipulating historical data and for establishing relationships and patterns among data in order to generate useful information for decision-making. The proposed research work presents various predictive analytic techniques that are useful for effective decision making and prediction. These techniques are used to improve prediction and decision making in many fields such as: weather prediction, marketing, business, medicine etc. In this work we have discussed four main predictive analytic techniques viz., Classification, Regression, Clustering and Association Analysis and their applications in various domains. Keywords: Data Mining, Predictive Analytics, Regression, Classification, Clustering and Association Analysis.
Cite this article:	Razeef Mohammad, Muheet Ahmed Butt, Majid Zaman , " Review of Predictive Analytic Modeling Techniques " , International Journal of Emerging Trends & Technology in Computer Science (IJETTCS), Volume 6, Issue 4, July - August 2017 , pp. 058-062 , ISSN 2278-6856.
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