Question

Present a real world example or from a journal paper which entails regularization technique and describe your findings based on the course materials with as much detail as possible. In your response to classmates, comment on an alternative business question that can be answered using the data they provided.

Answer 1

Before giving example for regularization, will give introduction and breif clarity of the concept of regularization.

REGULARIZATION: by seeing the name itself we can come to an opinion of generic as it sounds regular. In clearance, it is the concept of converting complex things into regular/ generic/ basic/ user freindly approach.

WHAT REGULARIZATION WILL DO?

regularization will resolve the overfitting problem in a model specially in a machine learning approach models or training sets.

here comes the doubt, what is OVERFITTING?

Overfitting is nothing but over dosed data/ irrelavant information above the limit, in simple words extra added data which is not at all useful and makes the original process complex.

HOW REGULARIZATION WORKS ?

Regularization is a technique, which is used to decrease the errors/ complex inputs to provide appropriate model/ smooth functioning on the given training set or model.

WHEN IT IS USED?

Regularization used in high variance conditions where the view will be of 2 parts such as BIAS and VARIANCE.

where Bias is a asssumption level and Variance is a original amount.

EXAMPLE:

Zip code is a best one to give example in a generic way.

zip code uses the L1 regularization, where L1 is a type of regularization used for making good amount of 0 weights and helps in selcting features. L1 regularization will be used when there is a good amount or lot of sparse features.

This a process of regularization starting from finding the errors , finding overfittings, making actions, re solving it, giving simplified data and presenting training set or model.

hope this answer is cleared for the positive knowledge in Regularization.

for regularization in depth knowledge you can refer google Machine Learning crash course.