学习率、隐藏层和Epoch在肺癌预测中的作用

2021 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS Pub Date : 2021-10-28 DOI:10.1109/ICIMCIS53775.2021.9699189

Yuni Widiastiwi, Dewi Hajar

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引用次数: 0

摘要

肺癌是世界上仅次于乳腺癌的最致命疾病之一，患病率为11.4%。这项研究旨在预测一个人是否被诊断患有疑似癌症的准确性。本研究中使用的方法使用了一个结合学习率、隐藏层和历元值的反向传播神经网络。结果表明，当学习率为0.1，隐层为100,epoch为1000时，预测准确率达到97%。

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Effect Of The Learning Rate, Hidden Layer, And Epoch In Lung Cancer Prediction

Lung cancer is one of the deadliest diseases in the world after breast cancer, with a prevalence rate of 11.4%. This research aims to predict the level of accuracy of whether a person is diagnosed with suspected cancer or not. The method used in this study uses a backpropagation neural network using a combination of the learning rate, hidden layer, and epoch values. The results showed that the learning rate value of 0.1, the value of hidden layer 100, and epoch 1000 resulted in predictions with the best accuracy value of 97%.

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2021 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS

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