Numerical Data Not Supported
I am trying to learn a couple of different methods for a numerical label.
I keep getting the error,
Error in: KernelNaiveBayes (KernelNaiveBayes) This learning scheme does not have sufficient capabilities for the given data set: numerical label not supported Each learning scheme has particular capabilities for data set handling. For example, some learners can only handle numerical attributes and can not learn from nominal attributes. Please perform a preprocessing step to transform your data set or use an alternative learning scheme. In case of a polynominal label attribute, i.e. a classification task with more than two classes, you can use a learning scheme capable only for binominal classes by wrapping a Binary2MultiClassLearner around the learning operator.
I have tried multiple different configurations of preprocessing the dataset with Binary2MultiClassLearner and other discretizations but each time I continue to get the error for numerical data. Can someone show the right configuration of how to "wrap a Binary2MultiClassLearner" around a learning operator?
My current configuration (without an attempt at a wrapper) is,