Question at position 22 What is the purpose of the activation function in an MLP?It determines the loss function used in the MLP. It controls the learning rate of the MLP algorithm.It provides the non-linearity of the MLP network. It determines the number of hidden layers in the MLP.

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BlackTom AI · Accepted Answer

The question asks about the purpose of the activation function in a multilayer perceptron (MLP), so we need to evaluate what each option implies about the role of activation functions.
Option 1: 'It determines the loss function used in the MLP.' This is incorrect because the loss function is chosen independently of the activation function; the loss measures error after the network outputs predictions, while the activation function shapes neuron outputs. The two are related but not determined by the activation function itself.
Option 2: 'It controls the learning rate of the MLP algorithm.' The learning rate is a parameter of the optimization algorithm (e.g., gradient descent) and is not governed by the activation function. Activation functions do not set or scale the step size used to update weights.
Option 3: 'It provides the non-linearity of the MLP network.' This is correct. Activation functions introduce non-linear transformations, enabling the network to model complex, non-linear relationships. Without non-linearity, an MLP would collapse into a linear model regardless of the number of layers.
Option 4: 'It determines the number of hidden layers in the MLP.' The number of hidden layers is a design choice in the network architecture, decided before training, and is not dictated by the activation function itself. Activation functions operate within those layers rather than setting their count.
Summarizing the reasoning: the activation function is the mechanism that injects non-linearity into neuron outputs, allowing the network to capture complex patterns. Other options misattribute roles to the activation function that actually belong to the loss function, the optimizer’s learning rate, or architectural design decisions rather than the activation mechanism.

Question at position 22 What is the purpose of the activation function in an MLP?It determines the loss function used in the MLP. It controls the learning rate of the MLP algorithm.It provides the non-linearity of the MLP network. It determines the number of hidden layers in the MLP.

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