A Data Science Central Community

Started Jan 5, 2012 0 Replies 0 Likes

I have built a PD model with the "Ever 90+ in 12 months of Performance Period" as Bad. Now I would like to derive PD for 6 months from the above, still Bad being "Ever 90+" but in 6 months of…Continue

Started Jun 10, 2011 0 Replies 0 Likes

DATA NEW;ARRAY A[10] A1-A10;ARRAY B[10] B1-B10;DO I = 1 TO 10;A[I] = ROUND(RANUNI(2));END;DO I = 1 TO 10;B[I] = MAX(OF A[1]-A[I]);END;RUN; I get an error using MAX function with arrays, any idea on…Continue

Sandeep Sunkara replied to RockyRambo's discussion WOE v/s using continuous variables as such

"I assume you use logistic regression post applying WOE transformation(?)!
X: Independent Variable
Y: Binary Dependent Variable
T(.): Transformation function
The fundamental assumption in logistic regression is 'X' and…"

Mar 24, 2012

Sandeep Sunkara posted a discussion### Scaling the PD wrt Performance Period

I have built a PD model with the "Ever 90+ in 12 months of Performance Period" as Bad. Now I would like to derive PD for 6 months from the above, still Bad being "Ever 90+" but in 6 months of performance.PD_90P_12 = Probability of becoming 90+ in next 12 months;PD_90P_06 = f(PD_90P_12) = Probability of becoming 90+ in next 06 months;How will I get the function "f";Any inputs? most welcome and thanks a lot!!See More

Jan 5, 2012

Sandeep Sunkara commented on Vincent Granville's blog post Identifying the number of clusters: finally a solution

"There is Cubic Clustering Criterion (CCC) available in PROC CLUSTER which helps in deciding the number of clusters.
@Vincent: I am little confused in going up to 4th derivative, since the plot is, when you smooth it, a second degree curve,…"

Oct 3, 2011

Sandeep Sunkara replied to Erdem Akkaş's discussion Effect of changes in attribute values

"Assuming no inter-dependency among the independent variables, checkout the correlations between target and each characteristic in both earlier time frame and current time frame. The variables that have drastic change in correlation over both the…"

Sep 19, 2011

Sandeep Sunkara replied to Panchanana M.R.L.N.'s discussion Validation of Cluster

"Hi Panchanana,
For your first question,
Variable Reduction for Numerical Variables can be done in two ways:
1. Before the Cluster Analysis(which again can be done in two ways):
(a) Use top N(choose as per the variation explained by the…"

Jun 11, 2011

Sandeep Sunkara posted a discussion### SAS Program

DATA NEW;ARRAY A[10] A1-A10;ARRAY B[10] B1-B10;DO I = 1 TO 10;A[I] = ROUND(RANUNI(2));END;DO I = 1 TO 10;B[I] = MAX(OF A[1]-A[I]);END;RUN; I get an error using MAX function with arrays, any idea on what is wrong in the above code?See More

Jun 10, 2011

Sandeep Sunkara replied to Hari's discussion Cut off point in logistic regression

"Yes it is.
If you have event rate of 10%, then the predicted probabilities will cluster around 0.1 and hence the cut-off point will also be arount 0.1.
If you have event rate of 70%, then the predicted probabilities will cluster around 0.7 and hence…"

Feb 15, 2011

- Field of Expertise:
- Predictive Modeling, Data Mining, Statistical Programming, Statistical Consulting

- Years of Experience in Analytical Role:
- 3

- Professional Status:
- Technical

- Interests:
- Finding a New Position, Networking

- Your Company:
- Dun and Bradstreet

- Industry:
- BFSI

- How did you find out about AnalyticBridge?
- Random Browsing

- No comments yet!

© 2019 AnalyticBridge.com is a subsidiary and dedicated channel of Data Science Central LLC Powered by

Badges | Report an Issue | Privacy Policy | Terms of Service

**Most Popular Content on DSC**

To not miss this type of content in the future, subscribe to our newsletter.

**Technical**

- Free Books and Resources for DSC Members
- Learn Machine Learning Coding Basics in a weekend
- New Machine Learning Cheat Sheet | Old one
- Advanced Machine Learning with Basic Excel
- 12 Algorithms Every Data Scientist Should Know
- Hitchhiker's Guide to Data Science, Machine Learning, R, Python
- Visualizations: Comparing Tableau, SPSS, R, Excel, Matlab, JS, Pyth...
- How to Automatically Determine the Number of Clusters in your Data
- New Perspectives on Statistical Distributions and Deep Learning
- Fascinating New Results in the Theory of Randomness
- Long-range Correlations in Time Series: Modeling, Testing, Case Study
- Fast Combinatorial Feature Selection with New Definition of Predict...
- 10 types of regressions. Which one to use?
- 40 Techniques Used by Data Scientists
- 15 Deep Learning Tutorials
- R: a survival guide to data science with R

**Non Technical**

- Advanced Analytic Platforms - Incumbents Fall - Challengers Rise
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- How to Become a Data Scientist - On your own
- 16 analytic disciplines compared to data science
- Six categories of Data Scientists
- 21 data science systems used by Amazon to operate its business
- 24 Uses of Statistical Modeling
- 33 unusual problems that can be solved with data science
- 22 Differences Between Junior and Senior Data Scientists
- Why You Should be a Data Science Generalist - and How to Become One
- Becoming a Billionaire Data Scientist vs Struggling to Get a $100k Job
- Why do people with no experience want to become data scientists?

**Articles from top bloggers**

- Kirk Borne | Stephanie Glen | Vincent Granville
- Ajit Jaokar | Ronald van Loon | Bernard Marr
- Steve Miller | Bill Schmarzo | Bill Vorhies

**Other popular resources**

- Comprehensive Repository of Data Science and ML Resources
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- 100 Data Science Interview Questions and Answers
- Cheat Sheets | Curated Articles | Search | Jobs | Courses
- Post a Blog | Forum Questions | Books | Salaries | News

**Archives**: 2008-2014 | 2015-2016 | 2017-2019 | Book 1 | Book 2 | More

**Most popular articles**

- Free Book and Resources for DSC Members
- New Perspectives on Statistical Distributions and Deep Learning
- Time series, Growth Modeling and Data Science Wizardy
- Statistical Concepts Explained in Simple English
- Machine Learning Concepts Explained in One Picture
- Comprehensive Repository of Data Science and ML Resources
- Advanced Machine Learning with Basic Excel
- Difference between ML, Data Science, AI, Deep Learning, and Statistics
- Selected Business Analytics, Data Science and ML articles
- How to Automatically Determine the Number of Clusters in your Data
- Fascinating New Results in the Theory of Randomness
- Hire a Data Scientist | Search DSC | Find a Job
- Post a Blog | Forum Questions