Machine Learning - Special issue on inductive transfer
Machine Learning for the Detection of Oil Spills in Satellite Radar Images
Machine Learning - Special issue on applications of machine learning and the knowledge discovery process
Context-sensitive learning methods for text categorization
ACM Transactions on Information Systems (TOIS)
A Batch Learning Vector Quantization Algorithm for Nearest Neighbour Classification
Neural Processing Letters
Learning to predict train wheel failures
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
IEEE Transactions on Knowledge and Data Engineering
Batch classification with applications in computer aided diagnosis
ECML'06 Proceedings of the 17th European conference on Machine Learning
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Data split into batches is very common in real-world applications. In speech recognition and handwriting identification, the batches are different people. In areas like oil spill detection and train wheel failure prediction, the batches are the particular circumstances when the readings were recorded. The recent research has proved that it is important to respect the batch structure when learning models for batched data. We believe that such a batch structure is also an opportunity that can be exploited in the learning process. In this paper, we investigated the novel method for dealing with the batched data. We applied the developed batch learning techniques to detect oil spills using radar images collected from satellite stations. This paper reports some progress on the proposed batch learning method and the preliminary results obtained from oil spills detection.