On modified boosting algorithm for geographic data applications

Michal Iwanowski; Jan Mulawka

doi:10.1117/12.2205625

11 September 2015 On modified boosting algorithm for geographic data applications

Michal Iwanowski, Jan Mulawka

Proceedings Volume 9662, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2015; 96623L (2015) https://doi.org/10.1117/12.2205625
Event: XXXVI Symposium on Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments (Wilga 2015), 2015, Wilga, Poland

Abstract

Boosting algorithms constitute one of the essential tools in modern machine-learning, one of its primary applications being the improvement of classifier accuracy in supervised learning. Most widespread realization of boosting, known as AdaBoost, is based upon the concept of building a complex predictive model out of a group of simple base models. We present an approach for local assessment of base model accuracy and their improved weighting that captures inhomogeneity present in real-life datasets, in particular in those that contain geographic information. Conducted experiments show improvement in classification accuracy and F-scores of the modified algorithm, however more experimentation is required to confirm the exact scope of these improvements.

Citation Download Citation

Michal Iwanowski and Jan Mulawka "On modified boosting algorithm for geographic data applications", Proc. SPIE 9662, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2015, 96623L (11 September 2015); https://doi.org/10.1117/12.2205625

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