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Classification Using Two Layer Neural Network Back Propagation Algorithm

Classification Using Two Layer Neural Network Back Propagation Algorithm
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摘要 Worldwide breast cancer is the most common form of cancer death occurring in 12.6% of women. This paper presents a cost effective approach to classify the normal, malignant and benign tumor using two layer neural network back propagation algorithm. Back propagation algorithm is used to train the neural network. Parallelization techniques speed up the computation process and as a result two layer neural networks outperform the previous work in terms of accuracy. Breast cancer tumor database used for the testing purpose is from the CIA machine learning repository. The highest accuracy of 97.12% is achieved using the two layer neural network back propagation algorithm. Worldwide breast cancer is the most common form of cancer death occurring in 12.6% of women. This paper presents a cost effective approach to classify the normal, malignant and benign tumor using two layer neural network back propagation algorithm. Back propagation algorithm is used to train the neural network. Parallelization techniques speed up the computation process and as a result two layer neural networks outperform the previous work in terms of accuracy. Breast cancer tumor database used for the testing purpose is from the CIA machine learning repository. The highest accuracy of 97.12% is achieved using the two layer neural network back propagation algorithm.
作者 K. A. Mohamed Junaid K. A. Mohamed Junaid(Department of Electronics & Instrumentation Engineering, R.M.K. Engineering College, Chennai, India)
出处 《Circuits and Systems》 2016年第8期1207-1212,共6页 电路与系统(英文)
关键词 Breast Cancer Back Propagation Neural Network MAMMOGRAM SONOGRAPHY Breast Cancer Back Propagation Neural Network Mammogram Sonography
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