nltk/nltk — Issue #132: Cross-Validation support
Author: alexrudnick
Created: 2012-01-17 06:26:48+00:00
State: open

A cross-validation module for all machine learning algorithms would be great. It's a standard procedure to report accuracy/precision/recall after performing cross-validation.

Migrated from http://code.google.com/p/nltk/issues/detail?id=615

earlier comments

StevenBird1 said, at 2010-12-22T23:56:58.000Z:

I wonder if there is enough functionality that could be abstracted in order to justify a cross-validation module. Is there a model we could adapt, perhaps in other machine learning toolkit? Also, how about discussing the requirements on nltk-dev?

mcenley said, at 2010-12-23T08:03:28.000Z:

Steven, There should be some functionality for cross validation: k-fold and leave-one-out. You would be a better man to judge "how" to go about it (module or adapting from scikits.learn). It would be great to brainstorm on nltk-dev. Let me know if I should post such a query on nltk-dev.