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Full-Text Articles in Databases and Information Systems
Temporal Data Classification Using Linear Classifiers, Peter Revesz, Thomas Triplet
Temporal Data Classification Using Linear Classifiers, Peter Revesz, Thomas Triplet
CSE Conference and Workshop Papers
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.
Adaptive Interpolation Algorithms For Temporal-Oriented Datasets, Jun Gao
Adaptive Interpolation Algorithms For Temporal-Oriented Datasets, Jun Gao
Department of Computer Science and Engineering: Dissertations, Theses, and Student Research
Spatiotemporal datasets can be classified into two categories: temporal-oriented and spatial-oriented datasets depending on whether missing spatiotemporal values are closer to the values of its temporal or spatial neighbors. We present an adaptive spatiotemporal interpolation model that can estimate the missing values in both categories of spatiotemporal datasets. The key parameters of the adaptive spatiotemporal interpolation model can be adjusted based on experience.