Prediction of humidity depending on temperature with low error rate using regression model

Abstract

This paper depicts prediction algorithm based on linear equations to forecast sequence trends in the future for time series data sets, prediction of humidity that dependent on temperature which is found in every 10 minutes. In this paper we analyze error rates during the prediction by using linear regression based algorithms. Two algorithms are discussed in this paper one for one dimensional stream data and second for two dimensional stream data. Both algorithms are applied on time series multivariate data sets and analysis of errors is to be done.