Data squashing: What is it? How can we improve it?
Matt Shotwell, PhD Vanderbilt University Medical Center
Data squashing is a aims to reduce the size of a data set, but preserve the information contained in it for the purposes of fitting a model. There are computational and other practical benefits of data squashing. Although several methods were developed more than 20 years ago, they have not been widely adopted. This may be due to practical limitations of these methods, which might be overcome with additional research. This seminar introduces the original method and some opportunities for improving the method to make it more widely applicable.