Tuning with respect to F1?

[danyaljj]

Is there a systematic way to tune a classifier's parameters (say output threshold etc) to maximize its F1?

[cowchipkid]

The NerBenchmark thingy I wrote was actually intended for such a purpose. Doing parameters sweeps of this nature is something I have seen people do before to improve results. However, for the NER benchmark, you had to create a configuration file for experiment you wanted to run, the you would have to go back and compare the results when all of them completed. I think it would be really cool to be able to specify a parameter, a range of values to run, and an increment and have the system just go and run them all.

On May 27, 2016, at 1:42 PM, Daniel Khashabi notifications@github.com wrote:

Is there a systematic way to tune a classifier's parameters (say output threshold etc) to maximize its F1?

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