Thammano, Arit

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Thammano, Arit
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Thammano, A.
Thummano, Arit
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arit.th@kmitl.ac.th

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    Adaptive Learning Rate for Dealing with Imbalanced Data in Classification Problems
    (2021-03-03)
    Jantanasukon, Ratanon
    ;
    Thammano, Arit
    This research modified a backpropagation learning algorithm in order to increase its ability to deal with imbalanced data problems. We used the backpropagation algorithm and a concept of multiple adaptive learning rates to train the feedforward neural network. Using multiple adaptive learning rates allowed us to achieve a classification model that had fewer problems when dealing with an imbalanced dataset the experimental results showed that the proposed method performed significantly better than the conventional backpropagation neural network in all tests.
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    Backpropagation Neural Network with Adaptive Learning Rate for Classification
    (2023-01-01)
    Jullapak, Rujira
    ;
    Thammano, Arit
    This research aims to improve the classification accuracy by modifying an original backpropagation neural network. In the proposed BPNN-ZMP, the learning rates were automatic tuned to improve the classification accuracy. Breast Cancer Coimbra dataset and Banknote Authentication dataset were used for testing the model performances. The results demonstrate that BPNN-ZMP improved over the original backpropagation neural network by 12.12 and 11.46% for Breast Cancer Coimbra dataset and Banknote Authentication dataset respectively. Although BPNN-ZMP could improve the model accuracy, the high accuracy in neural network backpropagation has been challenged in future work.