"Vincent. I'm not sure what the statistical basis behind this method is. Would you advocate jumbling all of the coefficients of a bad linear regression model until it led to an improved best r-square?
"I think your problem is that you've already oversampled your data and you want to compensate by using the weight statement. I would use the original data and then used the weight statement to perform the…"
"Lynne - This is a modeling contest and the judging criteria can be what ever they want it to be. Take a look at some of the evaluation criteria used by Kaggle and you will see why.
"Varun, I haven't used varclus for a while, but I would say that you could swap one variable for another if it made better business sense. The 1-R^2 ratio is only a guide. Also, look at the relationship between the 2 candidate variables.…"
"Sounds like your prospect is uninformed about the criteria for a good predictive model. But then again, a lot of clients can be swayed by these model "competitions" (e.g. Netflix), in which the best model is judged via simple…"
"Among these 8 worst techniques are the 5 BEST techniques (including linear regression). Why? They have stood the test of time and even today can be used to solve most of the worlds statistical problems. If you take the time to learn and…"
"Vincent. I think you place too much trust in the machines. Even if you do not know the intricacies of GLM, you still need to utilize the fact that X**2 is typically greater than x*2 when developing or interpreting a statistical model, a…"
Senior level Data Analyst, Data Miner, and Applications Programmer/Developer with over 10 years experience. I have a strong knowledge of BI, OLAP, data analytics, data mining, SAS, forecasting, relational databases, statistical procedures, logistic regression, predictive data modeling, and database marketing. I have worked with many different databases and operating systems.
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