Attribute Selection Methods Comparison for Classification of Diffuse Large B-Cell Lymphoma

The most important subtype of non-Hodgkin-s lymphoma is the Diffuse Large B-Cell Lymphoma. Approximately 40% of the patients suffering from it respond well to therapy, whereas the remainder needs a more aggressive treatment, in order to better their chances of survival. Data Mining techniques have helped to identify the class of the lymphoma in an efficient manner. Despite that, thousands of genes should be processed to obtain the results. This paper presents a comparison of the use of various attribute selection methods aiming to reduce the number of genes to be searched, looking for a more effective procedure as a whole.

Authors:

• Helyane Bronoski Borges
• Júlio Cesar Nievola

Keywords:

• Attribute selection
• data mining.

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