Incomplete Time Series Prediction Using Max-Margin Classification of Data with Absent Features
Joint Authors
Zhaowei, Shang
Taiping, Zhang
Shangjun, Ma
Fang, Bin
Lingfeng, Zhang
Source
Mathematical Problems in Engineering
Issue
Vol. 2010, Issue 2010 (31 Dec. 2010), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2010-06-29
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
This paper discusses the prediction of time series with missing data.
A novel forecast model is proposed based on max-margin classification of data with absent features.
The issue of modeling incomplete time series is considered as classification of data with absent features.
We employ the optimal hyperplane of classification to predict the future values.
Compared with traditional predicting process of incomplete time series, our method solves the problem directly rather than fills the missing data in advance.
In addition, we introduce an imputation method to estimate the missing data in the history series.
Experimental results validate the effectiveness of our model in both prediction and imputation.
American Psychological Association (APA)
Zhaowei, Shang& Lingfeng, Zhang& Shangjun, Ma& Fang, Bin& Taiping, Zhang. 2010. Incomplete Time Series Prediction Using Max-Margin Classification of Data with Absent Features. Mathematical Problems in Engineering،Vol. 2010, no. 2010, pp.1-14.
https://search.emarefa.net/detail/BIM-477641
Modern Language Association (MLA)
Zhaowei, Shang…[et al.]. Incomplete Time Series Prediction Using Max-Margin Classification of Data with Absent Features. Mathematical Problems in Engineering No. 2010 (2010), pp.1-14.
https://search.emarefa.net/detail/BIM-477641
American Medical Association (AMA)
Zhaowei, Shang& Lingfeng, Zhang& Shangjun, Ma& Fang, Bin& Taiping, Zhang. Incomplete Time Series Prediction Using Max-Margin Classification of Data with Absent Features. Mathematical Problems in Engineering. 2010. Vol. 2010, no. 2010, pp.1-14.
https://search.emarefa.net/detail/BIM-477641
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-477641