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How to handle error on Example Set label value in Random Forest
Learner I
Hello I am developing model using Radom Forest. I am very new to this. The error I have says "The learning scheme random forest does not have sufficient capabilities for handling an example set with only one label value."
I do have only one label value though there are 7 other attributes in my 6000 example data set. I believe this is allowed. What could be the error.
I do have only one label value though there are 7 other attributes in my 6000 example data set. I believe this is allowed. What could be the error.
0
Answers
the problem is that all your examples have the same label value, i.e. "yes".
A regular Random Forest can't handle that, there are some approaches of generating artificial outliers beforehand.
I.e. in Désir, C., Bernard, S., Petitjean, C., Heutte, L. (2012). A New Random Forest Method for One-Class Classification. In: , et al. Structural, Syntactic, and Statistical Pattern Recognition. SSPR /SPR 2012. Lecture Notes in Computer Science, vol 7626. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34166-3_31
You could try a one-class SVM instead or try to get data that contains outliers.
Greetings,
Jonas
If you are using Cross Validation, can you change it to Stratified Sampling?
Best would be if you could share your process.
Greetings,
Jonas
in the Sample Operator you have written a lowercase "o" instead of 0.
Greetings,
Jonas