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Weight Update And A Bias Update In A Single-Layer Perceptron Model

Why Update Weight?

Formula Of Weight Update

1. wi​ → weight of the ith input
2. η → learning rate (small constant like 0.01 or 0.1)
3. y → actual/true label
4. ŷ ​ → predicted output of the perceptron
5. xi ​ → input feature value

Example

1. Input x = [2,3]
2. Weights w = [0.5,0.2]
3. Actual y=1
4. Predicted ŷ = 0
5. Learning rate 0.1

Formula For Bias Update