Q5Soft Computing
Question
2 marks
Q.5. List out the steps in the perceptron learning algorithm for single output classes.
Answer
- Initialize weights and bias (commonly to zero or small random values) and set the learning rate.
- Present a training input pattern and compute the net input and output using the activation function.
- Compare the computed output to the target output; if they differ, update the weights and bias using the perceptron learning rule.
- Repeat over all training patterns until no weight changes occur (convergence) or a maximum epoch limit is reached.