Abstract
The purpose of the present work is to compare three classifiers: Fisher's Linear Discriminant Analysis, Multilayer Perception and Support Vector Machine to diagnosis of lung nodule. These algorithms are tested on a database with 36 nodules, being 29 benigns and 7 malignants. Results show that the three algorithms had similar performance on this particular task. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Silva, A. C., De Paiva, A. C., & De Oliveira, A. C. M. (2005). Comparison of FLDA, MLP and SVM in diagnosis of lung nodule. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3587 LNAI, pp. 285–294). Springer Verlag. https://doi.org/10.1007/11510888_28
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