What are the hidden layers of a feedforward neural network called?Select one:a.Input layersb.Hidden layersc.Output layersd.None of the above

The correct answer is b. Hidden layers.

Explanation

In a feedforward neural network, the architecture consists of three main types of layers: input layers, hidden layers, and output layers.

1. Input Layer: This layer is where the data enters the neural network. Each node in this layer represents a feature of the input data.

2. Hidden Layers: These layers are called "hidden" because they are not directly observable from the input or output. They perform computations and transformations on the data received from the input layer and the output from previous hidden layers. The number of hidden layers and the number of neurons in each layer can greatly affect the performance of the neural network.

3. Output Layer: This is the final layer that produces the output of the neural network, which can be a class label in classification tasks or a real number in regression tasks.

In summary, the hidden layers play a fundamental role in enabling the network to learn complex functions and representations from the input data. Thus, option b is the correct choice.