Asian Research Journal of Current Science

In this research investigation, the authors have proposed an All Possible Sets Ensemble Linear Regression Scheme. In this case, all possible sets are considered and their predictors for a particularly considered future co-ordinate are evaluated. We again pro-rate these thusly found future values using an Inner Product value obtained by the normalized vector consisting of all the points of the given dataset under linear regression analysis (arranged in a chronological order) along with its future prediction value of the afore-considered future time co-ordinate of concern and any set normalized vector among the all possible sets of the data co-ordinates (also arranged in chronological order only that the missing points shall be denoted by zero) along with its future prediction value of the afore-considered future time co-ordinate of concern, in the computation of the Ensemble Weighted Average. The entire computational analysis is performed in an R Programming Software environment. For this analysis to be applicable with low computational complexity, the authors condense the data set to extract a Sub-Set from the given data set using a presented special data splitting novel criterion, for conducting the aforementioned analysis.