Survey on Statistical Prediction Models Based on Intelligent Learning

Abstract

Developments in data oriented technology is increasing rapidly. Fact that data is the only asset that is in abundance has enabled a gateway across major developments in field of automation and smartness. Customized models for predicting people’s choices as well as decisions have been made much easier. Statistical prediction models based upon available user data are devised. Machine learning is a developing field that provide computers a new level of intelligence thereby evolving new fields of research such as image recognition, character recognition, voice recognition etc. This paper provides a tutorial scheme for all those aiming to brush their intellect on machine intellectual behavior and further deep learning based models. Detailed description of regression and classification algorithms will explain the background statistics that run behind any basic smart prediction model. Different learning models are casted for numerous problems.

Keywords: Supervised Learning, Unsupervised Learning, Linear Regression, Logistic Regression, Gradient Descent Algorithm