see function SMOTE in package DMwR hth Matthias On 31.03.2013 10:46, Nicolás Sánchez wrote:
I have a question about data mining. I have a dataset of 70 instances with 14 features that belong to 4 classes. As the number of each class is not enough to obtain a good accuracy using some classifiers( svm, rna, knn) I need to "oversampling" the number of instances of each class.I have heard that there is a method to do this. It consists in generating these new instances as follows: new_instance <---- original_instance + u(epsilon) U(epsilon) is a uniform number in the range [-epsilon,epsilon] and this number is applied to each feature of the dataset to obtain a new instance without modified the original class. Anybody has used this method to "oversampling" his data? Anybody has more information about it? Thanks in advance! [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
-- Prof. Dr. Matthias Kohl www.stamats.de ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
