Research of neural network classifier based on FCM and PSO for breast cancer classification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86092953" target="_blank" >RIV/61989100:27240/12:86092953 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1007/978-3-642-28942-2_58" target="_blank" >http://dx.doi.org/10.1007/978-3-642-28942-2_58</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-642-28942-2_58" target="_blank" >10.1007/978-3-642-28942-2_58</a>

Result language
angličtina
Original language name
Research of neural network classifier based on FCM and PSO for breast cancer classification
Original language description
Breast cancer is one of the most common tumors related to death in women in many countries. In this paper, a novel neural network classification model is developed. The proposed model uses floating centroids method and particle swarm optimization algorithm with inertia weight as optimizer to improve the performance of neural network classifier. Wisconsin breast cancer datasets in UCI Machine Learning Repository are tested with neural network classifier of the proposed method. Experimental results show that the developed model improves search convergence and performance. The accuracy of classification of benign and malignant tumors could be improved by the developed method compared with other classification techniques. 2012 Springer-Verlag.
Czech name
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Czech description
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Publication year
2012
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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