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BR Deshpande
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BR Deshpande replied to AKJ's discussion Examining correlation
"Since you are dealing with categorical variables, and also since you have only two, chi-square test of independence would be an automatic choice for simplicity of application and interpretation. If you want more details, you can find some…"
Sep 18, 2013
BR Deshpande commented on Vincent Granville's blog post The curse of big data
"Great article! I agree totally that in a larger dataset the probabilities of finding spurious/accidental correlations are higher than in a smaller dataset. In this context, "larger" implies higher k. But when you state "curse of big…"
Aug 16, 2013
BR Deshpande replied to Mark Nasila (PhD)'s discussion Handling Imbalanced data when building regression models
"Hi Steven Thanks for your explanation. We have also struggled with this issue and when we tried support vector machines, they were quite sensitive to imbalanced data. We balanced the data by undersampling but the results were sub-par. I am not sure…"
Apr 18, 2013
BR Deshpande commented on Vincent Granville's blog post The next revolution in analytics: it's not about software, it's about data
"I second this opinion. There are also a couple of excellent discussion items in the LinkedIn sister group which indicate this trend among practioners. One key challenge that people seem to be facing is determining answers to qustions like what data…"
Nov 19, 2010
BR Deshpande replied to Vincent Granville's discussion How can a large company detect the root cause for a sudden increase in churn, requested credits or charge backs?
"Hi Tom, Appreciate the response. Thanks. Are you (or anyone) aware of the performance of such models? We have used several models/techniques, but unfortunately, the speed of business limits us from really quantifying the ROI and helping us…"
Nov 17, 2010
BR Deshpande replied to Vincent Granville's discussion How can a large company detect the root cause for a sudden increase in churn, requested credits or charge backs?
"A related CRM question: what types of modeling techniques are commonly used to *predict* churn as opposed to explaining root causes post facto? Does anyone have benchmarks about such cases? Thanks."
Nov 16, 2010

Profile Information

Field of Expertise:
Business Analytics, Predictive Modeling, Data Mining, Biostatistics, Econometrics, Statistical Consulting, Medical Statistics
Years of Experience in Analytical Role:
12
Professional Status:
C-Level, Executive Management, Consultant
Interests:
Networking, New Venture
How did you find out about AnalyticBridge?
LinkedIn

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