Hey Sunita,
I understand that you want to know the use of regression model in ANN.
The regression model in an Artificial Neural Network (ANN) is used to predict the output value based on the input values. In your example, the output value is predicted based on the target value and the model coefficients. The purpose of the model is to learn the relationship between the input and output values, so that it can make accurate predictions for new input values. Knowing the predicted output value can be useful for evaluating the performance of the model and for making decisions based on the predicted values.
In an ANN, the regression model is trained using a process called backpropagation. This involves feeding the input values into the network, propagating the values forward through the network to generate a predicted output value, comparing the predicted output value to the actual output value, and then adjusting the model coefficients to minimize the difference between the predicted and actual values. This process is repeated many times using different input values to improve the accuracy of the model.
I hope this helps!
