Prediction technique for time series data sets using regression models

3Citations
Citations of this article
6Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Data mining techniques are the set of algorithms intended to find the hidden knowledge from the data sets, some of the popular techniques of data mining are prediction, sequential patterns, association, classification, clustering, and decision tree. Classification and regression are used for forecasting. Regression algorithms are based on various regression model i.e. linear regressions, non-linear regression, multiple regressions, logistic regression, and probabilistic regression. Forecasting of time series data sets with improved parameters has been discussed in the proposed methodology. For preprocessing the data set, sliding window or classification algorithms are used. Then coefficients values for the regression model are identified to fit the regression model.

Cite

CITATION STYLE

APA

Sagar, P., Gupta, P., & Kashyap, I. (2019). Prediction technique for time series data sets using regression models. In Communications in Computer and Information Science (Vol. 955, pp. 480–488). Springer Verlag. https://doi.org/10.1007/978-981-13-3140-4_43

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free