Perceptron network with just input and output layer converges for linearly separable
cases only.
Logistic regression model and perceptron network are the same model.
Unlike Perceptron network, logistic regression model can converge for non-linear
decision boundary cases.
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By changing the activation function to logistic and by using gradient descent algorithm,
Perceptron network can be made to address non-linear decision boundary cases.
Fig: 1