Analysing various Regression Models for Data Processing
K. K. Baseer1, Vikram Neerugatti2, Sandhya Tatekalva3, Akella Amarendra Babu4
1Dr. K. K. Baseer, Associate Professor of IT & Member, Data Analytics Research Center, Sree Vidyanikethan Engg. College, Tirupati, India.
2Vikram Neerugatti, Research Scholar, Department of CSE, SVUCE, Sri Venkateswara University, Tirupati, India.
3Dr. Sandhya Tatekalva, Academic Consultant, Department of Computer Science, S.V. University, Tiruapti, India.
4Dr. Akella Amarendra Babu, Department of Computer Science and Engineering, St. Martin’s Engineering College, Telangana, India
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 731-736 | Volume-8 Issue-8, June 2019 | Retrieval Number: H6749068819/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: For modeling and analyzing several variables, many techniques are available among which in statistical modeling, regression analysis is one. Regression Analysis (RA) is utilized for prediction and determination, where its utilization has generous cover with the field of Artificial Intelligence. RA is a measurable procedure’s for assessing the relationship among variables (one dependent and one or more independent). Its helps us to predict and that is why it is also called as predictive analysis model. In this study, we had used vehicle data like velocity with which traffic move’s, gradient, actual velocity to predict the velocity profile of the vehicle. Also, we had analyzed various regression models like linear regression, multivariate linear regression and nonlinear regression. The outcome of this work is to write a function for every model that everyone can reuse that without using pre-defined functions in languages and plotting the given data to best fit for analyzing.
Keyword: Regression, Predictor, Dependent variable, Machine learning, Vehicle and Velocity.
Scope of the Article: Data Analytic.