  We describe and compare several post-correlation radio frequency interference
classification methods. As data sizes of observations grow with new and
improved telescopes, the need for completely automated, robust methods for
radio frequency interference mitigation is pressing. We investigated several
classification methods and find that, for the data sets we used, the most
accurate among them is the SumThreshold method. This is a new method formed
from a combination of existing techniques, including a new way of thresholding.
This iterative method estimates the astronomical signal by carrying out a
surface fit in the time-frequency plane. With a theoretical accuracy of 95%
recognition and an approximately 0.1% false probability rate in simple
simulated cases, the method is in practice as good as the human eye in finding
RFI. In addition it is fast, robust, does not need a data model before it can
be executed and works in almost all configurations with its default parameters.
The method has been compared using simulated data with several other mitigation
techniques, including one based upon the singular value decomposition of the
time-frequency matrix, and has shown better results than the rest.
