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Herman Jopia
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  • Honolulu, Hawaii
  • United States
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Shivi Bhatia liked Herman Jopia's blog post Optimal Binning for Scoring Modeling (R Package)
Jun 16, 2016
Daniel Seymore liked Herman Jopia's blog post Optimal Binning for Scoring Modeling (R Package)
Jun 3, 2015
Skyler Atnip liked Herman Jopia's blog post Optimal Binning for Scoring Modeling (R Package)
Feb 27, 2015
Mark Locatelli left a comment for Herman Jopia
"Hi Herman! Thank you for the links to sbmining.  I learned a lot about Information Value and other measures of discretization quality. Cheers, Mark"
Feb 26, 2015
Tomas Keller liked Herman Jopia's blog post Optimal Binning for Scoring Modeling (R Package)
Feb 26, 2015
yang zhang liked Herman Jopia's blog post Optimal Binning for Scoring Modeling (R Package)
Feb 26, 2015
Nissim Matatov liked Herman Jopia's blog post Optimal Binning for Scoring Modeling (R Package)
Feb 26, 2015
Barrett Gady liked Herman Jopia's profile
Feb 25, 2015
Mark Locatelli liked Herman Jopia's blog post Optimal Binning for Scoring Modeling (R Package)
Feb 24, 2015
Herman Jopia's blog post was featured

Optimal Binning for Scoring Modeling (R Package)

The R Package smbinning categorizes a numeric variable into bins (intervals) for its ulterior usage in scoring modeling. The theory behind it falls within a branch of Machine Learning called Supervised Discretization, a categorization technique that divides a continuous variable into a small number of intervals mapped to a discrete target variable. For example, time since an account was open (Integer in Months) and the credit performance (Good/Bad), as shown in Table 1.…See More
Feb 24, 2015
Livan Alonso liked Herman Jopia's blog post Optimal Binning for Scoring Modeling (R Package)
Feb 22, 2015
Herman Jopia posted a blog post

Optimal Binning for Scoring Modeling (R Package)

The R Package smbinning categorizes a numeric variable into bins (intervals) for its ulterior usage in scoring modeling. The theory behind it falls within a branch of Machine Learning called Supervised Discretization, a categorization technique that divides a continuous variable into a small number of intervals mapped to a discrete target variable. For example, time since an account was open (Integer in Months) and the credit performance (Good/Bad), as shown in Table 1.…See More
Feb 22, 2015

Profile Information

Short Bio
8+ years of experience in retail banking leading the analytic units of Marketing and Credit Risk, developing and managing several data-driven projects such as credit scoring and credit loss models; forecasting, budgeting, and monitoring key performance metrics of the portfolio, and reporting on a regular basis to top management and regulators.
My Web Site Or LinkedIn Profile
http://www.linkedin.com/in/hjopia/en
Field of Expertise
Analytics
Professional Status
VP
Industry:
Banking
Interests:
Other

Herman Jopia's Blog

Optimal Binning for Scoring Modeling (R Package)

Posted on February 22, 2015 at 12:01am 0 Comments

The R Package smbinning categorizes a numeric variable into bins (intervals) for its ulterior usage in scoring modeling. The theory behind it falls within a branch of Machine Learning called Supervised Discretization, a categorization technique that divides a continuous variable into a small number of intervals mapped to a discrete target…

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At 11:49am on February 26, 2015, Mark Locatelli said…

Hi Herman!

Thank you for the links to sbmining.  I learned a lot about Information Value and other measures of discretization quality.

Cheers,

Mark

 
 
 

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