Framework for Predictive Analytics as a Service using ensemble model

Cloud computing offers service delivery models that facilitate users during development, execution and deployment of workflows. In this Big-data era, Organizations require value out of big data. For this they need not have to deploy complex infrastructure, but can use services that provide value. As such there is a need for a flexible and scalable service called Predictive Analytics as a Service (PAaaS). Predictive analytics can forecast trends, determines statistical probabilities and to act upon fraud and security threats for big data applications such as business trading, fraud detection, crime investigation, banking, insurance, enterprise security, government, healthcare, e-commerce, and telecommunications Prediction algorithms can be supervised or unsupervised with different configurations, and the optimal one may be different for each kind of data. This paper summarizes existing service frameworks for big data and proposes PAaaS framework that can be used by business to deal with prediction in big data. This proposed framework is based upon ensemble model that uses best out of prediction algorithms such as Artificial Neural Networks (ANN), Auto Regression algorithm(ARX) and Gaussian process(GP).