GDL

Proceeding from gdlhub / 2020-12-04 15:05:07
Oleh : Jasmir, Siti Nurmaini, Reza Firsandaya Malik, Dodo Zaen, Firdausal Abidin; Ahmad Zarkasi; Yesi Novaria Ku, Universitas Dinamika Bangsa
Dibuat : 2020-12-04, dengan 1 file

Keyword : breast cancer, deep learning, multilayer perceptron, classification
Url : http://ieeexplore.ieee.org/abstract/document/8605180/authors#authors

Breast cancer has been identified as the most widespread cancer amongst women and also the major cause of female cancer death all over the world. In this paper, we build the classification model of a person who is exposed to breast cancer based on recurrences-event and no-recurrences event. This classification using datasets from the University of Medicine Center, Institute Of Oncology, Ljublijana, Yugoslavia of the 286 datasets consist 2 classes, 201 No-Recurrences-Events classes, 85 Recurrences-events classes and 10 attributes including classes. The algorithm used for breast cancer classification is the Multilayer Perceptron algorithm with the accuracy level of 96.5% and high evaluation is 69.93% in 8-fold cross validation from 10-fold cross validation.

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