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ANINDO CHAKRABORTY
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  • Minneapolis, MN
  • United States
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ANINDO CHAKRABORTY's Discussions

Clustering with non numeric data

Started this discussion. Last reply by Kunal Dash May 24. 33 Replies

 

ANINDO CHAKRABORTY's Page

Latest Activity

Kunal Dash replied to ANINDO CHAKRABORTY's discussion Clustering with non numeric data
"Hello Indar,  Can you please give me a R implementation example of Conceptual clustering? "
May 24
Sarbani replied to ANINDO CHAKRABORTY's discussion Clustering with non numeric data
"Did you use a normal princomp or any special cases,what would be the best method to do variable clustering on binary data???"
Jul 18, 2014
ratheen chaturvedi replied to ANINDO CHAKRABORTY's discussion Clustering with non numeric data
"Anindo can you please share what you did"
Feb 26, 2013
ANINDO CHAKRABORTY replied to Biswajit Pal's discussion How to reduce high concordance (more than 85) in logistic regression model?
"From my experience I don't know why a high concordance would not be recommended. On the contrary - it is a indicator that the model you built is a good one!"
Aug 29, 2010
Tom Peters replied to ANINDO CHAKRABORTY's discussion Clustering with non numeric data
"Thx Ralph. I am new to SAS, so I will look into this."
Aug 28, 2010
Ralph Winters replied to ANINDO CHAKRABORTY's discussion Clustering with non numeric data
"Tom, I have had the same situation when using Proc LCA for latent class analysis. What I usually do is run a data step before, and manually recode into binaries. If you know SAS macros, that helps. -Ralph Winters"
Aug 28, 2010
Tom Peters replied to ANINDO CHAKRABORTY's discussion Clustering with non numeric data
"Hi, I realize this thread has been running for some time, but I am new to ABridge. I have uses Multiple Correspondence Analysis and then Hierarchical clustering on the dimensions scores using SPAD software, as mentioned earlier by some one else. In…"
Aug 27, 2010
Tom Peters replied to ANINDO CHAKRABORTY's discussion Clustering with non numeric data
"Vinay, you should dump out the cluster ID by record and then run a serious of focused crosstabs. That is the only way..."
Aug 27, 2010

Profile Information

Short Bio:
9 & 1/2 yrs analytics professional with experience in SAS, Predictive modeling, Developing Classifiers, Analytics Insights.

I began with GE Money working as a risk analyst for credit cards. In this position I built several predictive models making good use out of the logistic regression technique. I also built many segmentation models using CHAID and CART for risk management strategies. I moved out of GE Money after 6 years as a Business Manager in the portfolio risk team. My primary tool was SAS.

I joined a very well renowned retailer in their Analytics team. Here I am a Business Manager leading analytics team for stores, merchandising, finance etc. I have gained more experience in segmentation and modeling techniques for different aspects of retail. I am currently trying to work on some forecasting methods viz. ARIMA. Here too my primary tool is SAS.

My favorite area is classical regression methods. Although there are not many areas where this cannot be used, there are several developments in this field which I try to explore. I am in the process of gaining expertise in forecasting systems.
Field of Expertise:
Business Analytics, Predictive Modeling, Data Mining, Econometrics, Statistical Programming, Statistical Consulting, Finance
Years of Experience in Analytical Role:
9.5
Professional Status:
Manager
Interests:
Finding a New Position, Networking, Recruiting
Your Company:
Target
Industry:
Retail

Comment Wall (1 comment)

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At 3:02pm on June 28, 2009, Bruno M said…
Hi Anindo, I wonder how this project is going? I am relatively new to all of this, and the discussions on this site have been invaluable. I wonder if the tools I suggested (I linked to a list of open source data mining tools, KNIME, Orange (AI Labs), Weka, RapidMinder) have been helpful at all, or whether maybe I was way off on recommending them in the first place (if so i apologize!). Best Regards, Bruno
 
 
 

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