Linear Regression Coefficients problem
Hi, I'm relatively new to RapidMiner and have come across something that I do not understand in a linear regression model.
的issue is on the output - the model has 4 predictor variables (Population, Births, Wine Consumption, Liquor Consumption) and the output variable of Cirrhosis_DeathRate. The Cirrhosis_DeathRate is selected as a label in the Select Attributes operator. However, on running Rapid Miner only produces coefficients for Births, Wine Consumption and Liquor Consumption but not for Population.
I've run the same analysis in the data analysis pack in Excel and whilst the p-value for Population is not significant its not worse than liquor consumption which is showing in the RM output. Subsequently I'm at a bit of a loss as to why the population coefficient is not being calcuated. In addition population ~ Cirrhosis DeathRate is showing a relatively strong (0.7569) showing in the correlation matrix.
Any suggestions would be gratefully accpeted.
Thanks
Matt
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Best Answer
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earmijo MemberPosts:270Unicorn
By default, Rapidminer tries to do some feature selection. Some of the variables may be dropped. That's what's occuring to you. In "Feature Selection" choose "None". Then you'll get coefficients for all variables.
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Answers
Perfect. Many thanks for that. Much appreciated!