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A REVIEW ON PREDICTIVE ANALYTICS IN DATA MINING

A REVIEW ON PREDICTIVE ANALYTICS IN DATA MINING
Kavya.V1, Arumugam.S2
1M.E.Scholar, Department of Computer Science & Engineering, Nandha Engineering College, Erode-638052, Tamil Nadu, India
2Professor, Department of Computer Science & Engineering, Nandha Engineering College, Erode-638052, Tamil Nadu, India

ABSTRACT

The data mining its main process is to collect, extract and store the valuable information and now-a-days it’s done by many enterprises actively. In advanced analytics, Predictive analytics is the one of the branch which is mainly used to make predictions about future events which are unknown. Predictive analytics which uses various techniques from machine learning, statistics, data mining, modeling, and artificial intelligence for analyzing the current data and to make predictions about future. The two main objectives of predictive analytics are Regression and Classification. It is composed of various analytical and statistical techniques used for developing models which predicts the future occurrence, probabilities or events. Predictive analytics deals with both continuous changes and discontinuous changes. It provides a predictive score for each individual (healthcare patient, product SKU, customer, component, machine, or other organizational unit, etc.) to determine, or influence the organizational processes which pertain across huge numbers of individuals, like in fraud detection, manufacturing, credit risk assessment, marketing, and government operations including law enforcement.

KEYWORDS

Predictive analytics, Credit history, forecasting, Regression techniques 





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