Unlike other articles, I found the wikipedia entry for this subject unreadable for a non-math person (like me).
I understood the basic idea, that you favor models with fewer rules. What I don't get is how do you get from a set of rules to a 'regularization score' which you can use to sort the models from least to most overfit.
Can you describe a simple regularization method?
I'm interested in the context of analyzing statistical trading systems. It would be great if you could describe if/how I can apply regularization to analyze the following two predictive models:
Model 1 - price going up when:
- exp_moving_avg(price, period=50) > exp_moving_avg(price, period=200)
Model 2 - price going up when:
- price[n] < price[n-1] 10 times in a row
- exp_moving_avg(price, period=200) going up
But I'm more interested in getting a feeling for how you do regularization. So if you know better models for explaining it please do.