A comparative analysis on linear regression and support vector regression

In business, consumers interest, behavior, product profits are the insights required to predict the future of business with the current data or historical data. These insights can be generated with the statistical techniques for the purpose of forecasting. The statistical techniques can be evaluated for the predictive model based on the requirements of the data. The prediction and forecasting are done widely with time series data. Most of the applications such as weather forecasting, finance and stock market combine historical data with the current streaming data for better accuracy. However the time series data is analyzed with regression models. In this paper, linear regression and support vector regression model is compared using the training data set in order to use the correct model for better prediction and accuracy.

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