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Predictive Analytics: A Review of Trends and Techniques
Author(s) -
Vaibhav Kumar,
Lei Mo
Publication year - 2018
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2018917434
Subject(s) - computer science , analytics , data science
Predictive analytics is a term mainly used in statistical and analytics techniques. This term is drawn from statistics, machine learning, database techniques and optimization techniques. It has roots in classical statistics. It predicts the future by analyzing current and historical data. The future events and behavior of variables can be predicted using the models of predictive analytics. A score is given by mostly predictive analytics models. A higher score indicates the higher likelihood of occurrence of an event and a lower score indicates the lower likelihood of occurrence of the event. Historical and transactional data patterns are exploited by these models to find out the solution for many business and science problems. These models are helpful in identifying the risk and opportunities for every individual customer, employee or manager of an organization. With the increase in attention towards decision support solutions, the predictive analytics models have dominated in this field. In this paper, we will present a review of process, techniques and applications of predictive analytics.

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