A computing method of predictive value based on fitting function in linear model

Zhong, Hao and Zhang, Huibing and Jia, Fei (2020) A computing method of predictive value based on fitting function in linear model. EAI Endorsed Transactions on Collaborative Computing. e2. ISSN 2312-8623

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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.

Item Type: Article
Uncontrolled Keywords: linear model, linear fitting, fitting function, predictive value
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
QA75 Electronic computers. Computer science
T Technology > T Technology (General)
Depositing User: EAI Editor IV
Date Deposited: 15 Jul 2021 11:32
Last Modified: 15 Jul 2021 11:32
URI: https://eprints.eudl.eu/id/eprint/4677

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