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- W3048659936 abstract "Abstract:Machine learning has various applications.Machine learning model has two problems.OverfittingandUnderfitting.Underfitting is a statistical model or a machinelearning algorithm,it cannot capture the underlying trend ofthe data.A statistical model is said to be overfitted, when it istrained with a lot of data.When model has trained on fewerfeatures, the machine will be too biased, and then the modelgets underfitting problem. So, it is needed to train the modelon more features and there is one more problemoccurs.Overfitting problem can be reduced by usingregularization functions and data augmentation. In theprevious research on activation functions, Hock HungChieng Proposed an activation function called Flatten-TSwish: a thresholdReLU, which is a multiplication of Reluand sigmoid function.Index Terms: Flatten-T swish, Machine learning, activationfunction" @default.
- W3048659936 created "2020-08-18" @default.
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- W3048659936 date "2020-06-01" @default.
- W3048659936 modified "2023-10-18" @default.
- W3048659936 title "Reducing Overfitting Problem in Machine Learning using L1/4 Activation Function" @default.
- W3048659936 doi "https://doi.org/10.32377/cvrjst1820" @default.
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