FEATURE SELECTION USING GENETIC ALGORITHM FOR BREAST CANCER DIAGNOSIS: EXPERIMENT ON THREE DIFFERENT DATASETS

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AALAEI SHOKOUFEH; SHAHRAKI HADI; ROWHANIMANESH ALIREZA; ESLAMI SAEID

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Journal: Iranian Journal of Basic Medical Sciences Year:2016 | Volume:19 | Issue:5 Page(s): 476-482

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Information Journal Paper

Title

FEATURE SELECTION USING GENETIC ALGORITHM FOR BREAST CANCER DIAGNOSIS: EXPERIMENT ON THREE DIFFERENT DATASETS

Author(s)

AALAEI SHOKOUFEH | SHAHRAKI HADI | ROWHANIMANESH ALIREZA | ESLAMI SAEID | Issue Writer Certificate

Keywords

BREAST CANCER

CLASSIFICATION FEATURE

SELECTION DATA MINING

Abstract

Objective (s): This study addresses feature selection for BREAST CANCER diagnosis. The present process uses a wrapper approach using GA-based on feature selection and PS-classifier. The results of experiment show that the proposed model is comparable to the other models on Wisconsin BREAST CANCER datasets.Materials and Methods: To evaluate effectiveness of proposed feature selection method, we employed three different classifiers artificial neural network (ANN) and PS-classifier and genetic algorithm based classifier (GA-classifier) on Wisconsin BREAST CANCER datasets include Wisconsin BREAST CANCER dataset (WBC), Wisconsin diagnosis BREAST CANCER (WDBC), and Wisconsin prognosis BREAST CANCER (WPBC).Results: For WBC dataset, it is observed that feature selection improved the accuracy of all classifiers expect of ANN and the best accuracy with feature selection achieved by PS-classifier. For WDBC and WPBC, results show feature selection improved accuracy of all three classifiers and the best accuracy with feature selection achieved by ANN. Also specificity and sensitivity improved after feature selection.Conclusion: The results show that feature selection can improve accuracy, specificity and sensitivity of classifiers. Result of this study is comparable with the other studies on Wisconsin BREAST CANCER datasets.

Cites

The Precision of Neonatal Birth Outcomes Prediction Using the Bagging Neural Network

References

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APA: Copy

AALAEI, SHOKOUFEH, SHAHRAKI, HADI, ROWHANIMANESH, ALIREZA, & ESLAMI, SAEID. (2016). FEATURE SELECTION USING GENETIC ALGORITHM FOR BREAST CANCER DIAGNOSIS: EXPERIMENT ON THREE DIFFERENT DATASETS. IRANIAN JOURNAL OF BASIC MEDICAL SCIENCES, 19(5), 476-482. SID. https://sid.ir/paper/696082/en

Vancouver: Copy

AALAEI SHOKOUFEH, SHAHRAKI HADI, ROWHANIMANESH ALIREZA, ESLAMI SAEID. FEATURE SELECTION USING GENETIC ALGORITHM FOR BREAST CANCER DIAGNOSIS: EXPERIMENT ON THREE DIFFERENT DATASETS. IRANIAN JOURNAL OF BASIC MEDICAL SCIENCES[Internet]. 2016;19(5):476-482. Available from: https://sid.ir/paper/696082/en

IEEE: Copy

SHOKOUFEH AALAEI, HADI SHAHRAKI, ALIREZA ROWHANIMANESH, and SAEID ESLAMI, “FEATURE SELECTION USING GENETIC ALGORITHM FOR BREAST CANCER DIAGNOSIS: EXPERIMENT ON THREE DIFFERENT DATASETS,” IRANIAN JOURNAL OF BASIC MEDICAL SCIENCES, vol. 19, no. 5, pp. 476–482, 2016, [Online]. Available: https://sid.ir/paper/696082/en

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