document: A comparison of different decision algorithms used in volumetric storm cells classification Decision algorithms useful in classifying meteorological volumetric radar data are discussed . Such data come from the radar decision support system -LRB- RDSS -RRB- database of Environment Canada and concern summer storms created in this country . Some research groups used the data completed by RDSS for verifying the utility of chosen methods in volumetric storm cells classification . The paper consists of a review of experiments that were made on the data from RDSS database of Environment Canada and presents the quality of particular classifiers . The classification accuracy coefficient is used to express the quality . For five research groups that led their experiments in a similar way it was possible to compare received outputs . Experiments showed that the support vector machine -LRB- SVM -RRB- method and rough set algorithms which use object oriented reducts for rule generation to classify volumetric storm data perform better than other classifiers
doc_bio_tags: O O O O B I O O B I I I B I O O O B I I I O O O O O O O O B I I I O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O B I I I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I I O O O O O B I I O O B I I O O O O O O O O O O O O O
extractive_keyphrases: decision algorithms volumetric storm cells classification meteorological volumetric radar data radar decision support system summer storms classification accuracy support vector machine rough set algorithms object oriented reducts