Breast Cancer Analysis using Independent Component Analysis (ICA) and Self Organizing Map (SOM)
نویسنده
چکیده
A method for discrimination and classification of breast cancer dataset with benign and malignant tissues is proposed using Independent Component Analysis (ICA) and Self Organizing Map (SOM). The method implement ICA for preprocessing and data reduction and SOM for data analysis. The best performance was obtained with ICASOM, resulting in 98.8% classification accuracy and a SOM result is 94.9%.
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