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The ReLU activation function can introduce non-linearity to the model.Group of answer choicesTrueFalse

Question

The ReLU activation function can introduce non-linearity to the model.

Group of answer choices

  • True
  • False
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Solution

Final Answer

True.

The ReLU (Rectified Linear Unit) activation function does indeed introduce non-linearity to the model. It is defined as ReLU(x)=max(0,x) \text{ReLU}(x) = \max(0, x) , which means that it outputs zero for any input value less than or equal to zero and outputs the input value itself for any positive input. This characteristic allows neural networks to approximate complex functions and capture non-linear relationships in the data. By incorporating non-linearity, ReLU helps improve the learning capability of neural networks, making it a popular choice in deep learning architectures.

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