Which of the following is not the function of the Hidden layer in Neural Networks?
a) To display the result
b) Receive data from the Input Layer
c) Process the data
d) Give data to the output layer.
Answers
Answer:
give data to the output layer
Explanation:
according me hope it helps you yrrrrr
a) To display the result. The hidden layers in a neural network are not responsible for displaying the results. They receive data from the input layer, process it, and pass it on to the output layer, which then provides the final result. The hidden layer's purpose is to learn complex relationships between the inputs and outputs, allowing the neural network to perform more sophisticated processing and make more accurate predictions.
In a neural network, the hidden layer is sandwiched between the input layer and the output layer. It is called "hidden" because its values and calculations are not visible to the outside world. The hidden layer receives inputs from the input layer, applies its weights and biases to the inputs, and then passes the result through an activation function to produce its own outputs. These outputs are then passed on to the next layer, typically the output layer, for further processing.
One of the main functions of the hidden layer is to extract and represent complex relationships between the inputs and outputs in a form that can be learned and used for prediction. The hidden layer uses these representations to make predictions about the outputs based on the inputs. It does this by adjusting its weights and biases during the training process to minimize the error between the actual outputs and the predicted outputs.
In summary, the hidden layer plays a crucial role in the functioning of a neural network. Its ability to learn complex relationships and make accurate predictions is what makes neural networks so powerful and useful in various applications such as image recognition, natural language processing, and predictive analytics.
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