Momentum Backpropagation Optimization for Cancer Detection Based on DNA Microarray Data
International Journal of artificial intelligence research
View Publication Info| Field | Value | |
| Title |
Momentum Backpropagation Optimization for Cancer Detection Based on DNA Microarray Data
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| Creator |
Wisesty, Untari Novia
Sthevanie, Febryanti Rismala, Rita |
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| Subject |
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Momentum Backpropagation with Adaptive Learning Rate Neural Network Genetic Algorithm DNA Microarray Early Cancer Detection |
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| Description |
Early detection of cancer can increase the success of treatment in patients with cancer. In the latest research, cancer can be detected through DNA Microarrays. Someone who suffers from cancer will experience changes in the value of certain gene expression. In previous studies, the Genetic Algorithm as a feature selection method and the Momentum Backpropagation algorithm as a classification method provide a fairly high classification performance, but the Momentum Backpropagation algorithm still has a low convergence rate because the learning rate used is still static. The low convergence rate makes the training process need more time to converge. Therefore, in this research an optimization of the Momentum Backpropagation algorithm is done by adding an adaptive learning rate scheme. The proposed scheme is proven to reduce the number of epochs needed in the training process from 390 epochs to 76 epochs compared to the Momentum Backpropagation algorithm. The proposed scheme can gain high accuracy of 90.51% for Colon Tumor data, and 100% for Leukemia, Lung Cancer, and Ovarian Cancer data.
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| Publisher |
STMIK Dharma Wacana
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| Contributor |
—
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| Date |
2021-01-05
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| Type |
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion Peer-reviewed Article |
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| Format |
application/pdf
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| Identifier |
http://ijair.id/index.php/ijair/article/view/188
10.29099/ijair.v4i2.188 |
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| Source |
International Journal of Artificial Intelligence Research; Vol 4, No 2 (2020): December; 127 - 134
2579-7298 10.29099/ijair.v4i2 |
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| Language |
eng
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| Relation |
http://ijair.id/index.php/ijair/article/view/188/pdf
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| Rights |
Copyright (c) 2021 International Journal of Artificial Intelligence Research
https://creativecommons.org/licenses/by-sa/4.0 |
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