LogitBoost is now roughly twice as fast as before in the two-class case because the second model is not built (it should always predict the additive inverse of the first model.

git-svn-id: https://svn.cms.waikato.ac.nz/svn/weka@10869 e0a1b77d-ad91-4216-81b1-defd5f83fa92
Initial import

git-svn-id: https://svn.cms.waikato.ac.nz/svn/weka@10870 e0a1b77d-ad91-4216-81b1-defd5f83fa92
From Eibe: LogitBoost now implements IterativeClassifier. LogitBoost is now roughly twice as fast as before in the two-class case because the second model is not built (it should always predict the additive inverse of the first model.

git-svn-id: https://svn.cms.waikato.ac.nz/svn/weka@10871 e0a1b77d-ad91-4216-81b1-defd5f83fa92
Updated with IterativeClassifier

git-svn-id: https://svn.cms.waikato.ac.nz/svn/weka@10872 e0a1b77d-ad91-4216-81b1-defd5f83fa92
Fixed bug introduced in the last couple of commits concerning datasets consisting exclusively of a class attribute.

git-svn-id: https://svn.cms.waikato.ac.nz/svn/weka@10873 e0a1b77d-ad91-4216-81b1-defd5f83fa92
From Eibe: Fixed bug introduced in the last couple of commits concerning datasets consisting exclusively of a class attribute.

git-svn-id: https://svn.cms.waikato.ac.nz/svn/weka@10874 e0a1b77d-ad91-4216-81b1-defd5f83fa92