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Simple Machine Learning Approaches to Safety-Related Systems
| Type of publication: | Incollection |
| Citation: | moewes_simple_2008 |
| Booktitle: | Machine Interpretation of Patterns: Image Analysis and Data Mining |
| Series: | Statistical Science and Interdisciplinary Research |
| Volume: | 11 |
| Chapter: | 12 |
| Year: | 2010 |
| Month: | June |
| Pages: | 231--249 |
| Publisher: | World Scientific Publishing Co. Inc. |
| Address: | Hackensack, NJ, USA |
| ISBN: | 978-981-4299-18-3 |
| URL: | http://dx.doi.org/10.1142/9789... |
| DOI: | 10.1142/9789814299190_0012 |
| Abstract: | The principles of machine learning become gradually more interesting to safety-related applications. This paper introduces a preprocessing method for such kind of applications. Here we concentrate on scenarios with highly unbalance misclassification costs. Therefore we briefly introduce a variation of multiple-instance learning (MIL) and recall soft margin hyperplane classifiers. According to this classifier we present a training set selection method for multidimensional problems that combines the idea of support vector pruning with pattern weighting. The proposed method guarantees both high performance and interpretable decisions. The main advantage of our proposed filter method is the obtained training set that rather prefers quasilinear classifiers during model selection. We conclude with potential extensions for future research in this domain. |
| Keywords: | Multiple-Instance Learning, Safety-Related Systems, Support Vector Machine |
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| Added by: | [ADM] |
| Total mark: | 0 |
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