skll: SKLL 1.1.0

Implemented enhancements Base estimators other than default are not supported for AdaBoost(#238) Need cv_folds option(#222) Remove decision tree and random forest learners from requires_dense set(#207) stratification during cross-validation should be optional (#160) Fixed bugs Bug when checking if hasher_features is a valid option(#234) need to improve the way to check the validity of configuration file(#223) Stop modifying global numpy random seed(#220) Config file paths are relative to current working directory instead of config file location(#213) Closed issues cannot import name BaseLibLinear(#241)1) a line causing an error(#236) Changes based on big LibLinear refactoring in scikit-learn(#235) skll breaks importing missing class BaseLibLinear with scikit-learn 0.16(#233) Learner.model_params will return weights with the wrong sign if sklearn is fixed (#111) Merged pull requests Overhaul configuration file parsing (@desilinguist, #246) Several minor bugfixes (@desilinguist, #245) Compatibility with scikit-learn v0.16.1 (@desilinguist, #243) Expose cv_folds and stratified (@aoifecahill, #240) Adding Report tests (@brianray, #237) Full Changelo