Predictive analytics is the branch of data mining concerned with the prediction of future probabilities and trends. The central element of predictive analytics is the predictor, a variable that can be measured for an individual or other entity to predict future behavior. For example, an insurance company is likely to take into account potential driving safety predictors such as age, gender, and driving record when issuing car insurance policies. Multiple predictors are combined into a predictive model, which, when subjected to analysis, can be used to forecast future probabilities with an acceptable level of reliability. In predictive modeling, data is collected, a statistical model is formulated, predictions are made and the model is validated (or revised) as additional data becomes available. Predictive analytics are applied to many research areas, including meteorology, security, genetics, economics, and marketing. In this paper, we have done an extensive study on various predictive techniques with all its future directions and applications in various areas are being explained
Mishra, Debahuti; Das, Asit Kumar; Mausumi, Mausumi; and Mishra, Sashikala
"Predictive Data Mining: Promising Future and Applications,"
International Journal of Computer and Communication Technology: Vol. 2
, Article 5.
Available at: https://www.interscience.in/ijcct/vol2/iss3/5