"Compare model performance graphs"
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Marius
Thanks for the hints.... Still struggling with some of the concepts being new to data mining .
Yes I was looking for ROC curves for classification problems.
However conceptually trying this on the iris data set didn't work out because the label needs to be binomial instead of multiclass. So will have to manipulate my data set a bit to get the 'one vs the rest' labels. Some practical learning to be done there
Regards
Geoffrey
Thanks for the hints.... Still struggling with some of the concepts being new to data mining .
Yes I was looking for ROC curves for classification problems.
However conceptually trying this on the iris data set didn't work out because the label needs to be binomial instead of multiclass. So will have to manipulate my data set a bit to get the 'one vs the rest' labels. Some practical learning to be done there
Regards
Geoffrey
I suppose you already know how to evaluate a single model in RapidMiner, e.g. with the X-Validation. The X-Validation puts out a performance vector, which should contain the root mean squared error. This value is only a scalar value, so I don't know from which data you want to create curves. Of course you can compare the values from different models, and if you extract the performance values, you also can write them into a single example set for easier comparison.
For classification problems we can create ROC comparison charts.
For the performance curves, please give us a more detailed description of what you want to do. Please read the post linked in my signature on how to write good questions.
Happy Mining!
~Marius