How To Use Target Encoding in Machine Learning Credit Risk Models – Part 1
#mlcreditriskmodels #targetencoding #mlmodels #outputencoding #logisticregression #piecewiseconstantmodel #predictivemlmodelling #mlmodeloptimization
https://hackernoon.com/how-to-use-target-encoding-in-machine-learning-credit-risk-models-part-1
#mlcreditriskmodels #targetencoding #mlmodels #outputencoding #logisticregression #piecewiseconstantmodel #predictivemlmodelling #mlmodeloptimization
https://hackernoon.com/how-to-use-target-encoding-in-machine-learning-credit-risk-models-part-1
Hackernoon
How To Use Target Encoding in Machine Learning Credit Risk Models – Part 1 | HackerNoon
Discover how to use target encoding and weight of evidence for transforming categorical variables in supervised learning, enhancing model performance.
How To Use Target Encoding in Machine Learning Credit Risk Models - Part 2
#mlcreditriskmodels #targetencoding #woecode #pdqcut #whatistargetencoding #whatiswoe #userdefinedbins #bernoullidistribution
https://hackernoon.com/how-to-use-target-encoding-in-machine-learning-credit-risk-models-part-2
#mlcreditriskmodels #targetencoding #woecode #pdqcut #whatistargetencoding #whatiswoe #userdefinedbins #bernoullidistribution
https://hackernoon.com/how-to-use-target-encoding-in-machine-learning-credit-risk-models-part-2
Hackernoon
How To Use Target Encoding in Machine Learning Credit Risk Models - Part 2 | HackerNoon
In my previous story, we covered the derivation of the expression of WoE using maximum likelihood. Now, we will apply it practically on a random dataset