Research Article
A computing method of predictive value based on fitting function in linear model
@ARTICLE{10.4108/eai.2-10-2020.166542, author={Hao Zhong and Huibing Zhang and Fei Jia}, title={A computing method of predictive value based on fitting function in linear model}, journal={EAI Endorsed Transactions on Collaborative Computing}, volume={4}, number={14}, publisher={EAI}, journal_a={CC}, year={2020}, month={10}, keywords={}, doi={10.4108/eai.2-10-2020.166542} }- Hao Zhong
Huibing Zhang
Fei Jia
Year: 2020
A computing method of predictive value based on fitting function in linear model
CC
EAI
DOI: 10.4108/eai.2-10-2020.166542
Abstract
Linear models are common prediction models in collaborative computing, which mainly generates fitting function to express the relationship between feature vectors and predictive value. In the process of computing the predictive value according to the fitting function and feature vector, this paper mainly conducted the following researches. Firstly, this paper defines a change interval of predictive value according to training set. Secondly, in this paper, the change interval of predictive value corresponding to feature vector in test setis computed. Finally, according to distribution of training set in the changing interval, the predictive values corresponding to feature vectors in test set are computed. Standard data sets are used in experiment, and MAE(Mean Absolute Error) and RMSE(Root Mean Square Error) are used to evaluate the prediction results. The experimental results show that the method proposed in this paper can improve the prediction error to acertain extent.
Copyright © 2020 Hao Zhong et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
