How does regularized logistic regression regularize perceptron model?

[ntvy95]

In the case I use regularized logistic regression to train perceptron model with threshold , for regularized logistic regression it means that I have had soft-order constraint on , however for perceptron model, as suggested in Exercise 4.6, it looks like soft-order constraint on doesn't regularize perceptron model at all. Meanwhile in practice, I see that regularized logistic regression does regularize perceptron model and Andrew Ng's online course also suggests that regularized logistic regression fights against overfitting on classification problems.

What did I miss here?

Thank you very much in advance.

[htlin]

Originally Posted by ntvy95

In the case I use regularized logistic regression to train perceptron model with threshold , for regularized logistic regression it means that I have had soft-order constraint on , however for perceptron model, as suggested in Exercise 4.6, it looks like soft-order constraint on doesn't regularize perceptron model at all. Meanwhile in practice, I see that regularized logistic regression does regularize perceptron model and Andrew Ng's online course also suggests that regularized logistic regression fights against overfitting on classification problems.

What did I miss here?

Thank you very much in advance.

That is because the hard-classification output (sign) is not affected by the magnitude of while the soft output () is . Hope this helps.

[pdsubraa]

Happy New Year 2018! guys

Htlin - you always make my day precious with your solutions. No wonder you're great!

Thanks again!

[htlin]

Originally Posted by pdsubraa

Happy New Year 2018! guys

Htlin - you always make my day precious with your solutions. No wonder you're great!

Thanks again!

Thanks. Happy new year to everyone.