Hi all, I am doing binary classification and want to improve the classification results on imbalanced response data.
Currently the performance is poor. Are there ways I could improve the performance? I could either try different classification methodologies, or try exploring the data more, and throwing away noisy data, and manipulate the data more before sending into the classifiers. I was wondering are there systematic way of improving classification performance? I know it's an art. But I am lack of experience and want to gain experience. How to do that? Please give me some pointers about hands-on tutorial on classification. I am using R. Thank you! ______________________________________________ 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.
