Temporal data classification using linear classifiers

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摘要

Data classification is usually based on measurements recorded at the same time. This paper considers temporal data classification where the input is a temporal database that describes measurements over a period of time in history while the predicted class is expected to occur in the future. We describe a new temporal classification method that improves the accuracy of standard classification methods. The benefits of the method are tested on weather forecasting using the meteorological database from the Texas Commission on Environmental Quality and on influenza using the Google Flu Trends database.

论文关键词:Classification integration,Constraint database,Datalog,Data integration,Decision tree,Reclassification,SVM

论文评审过程:Available online 5 July 2010.

论文官网地址:https://doi.org/10.1016/j.is.2010.06.006