"using two queued Linear Regression models"
Hi everybody,
I am about to analysze data from the KDD98 (http://archive.ics.uci.edu/ml/databases/kddcup98/kddcup98.html) dataset. I use the “optimize parameters” operator, and within that a cross-validation. For training,I queued two linear regression models to predict a feature (label). The first LRM works on all features and I do not optimize any parameter, while the second LRM works only on 50 features and I optimize the ridge factor.
However, once I run the process and Rapidminer starts to execute the second LRM, the following error message pops up:
WARNING: Error during calculation: Matrix is singular.: Increasing ridge factor from 0.0 to 1.0E-7
Does anybody have an idea where this could come from or what I would have to change.
Thanks in advance!
Ralf
I am about to analysze data from the KDD98 (http://archive.ics.uci.edu/ml/databases/kddcup98/kddcup98.html) dataset. I use the “optimize parameters” operator, and within that a cross-validation. For training,I queued two linear regression models to predict a feature (label). The first LRM works on all features and I do not optimize any parameter, while the second LRM works only on 50 features and I optimize the ridge factor.
However, once I run the process and Rapidminer starts to execute the second LRM, the following error message pops up:
WARNING: Error during calculation: Matrix is singular.: Increasing ridge factor from 0.0 to 1.0E-7
Does anybody have an idea where this could come from or what I would have to change.
Thanks in advance!
Ralf