Release Notes for latest version of the MTI ML package for May 1, 2012.

• Classifier's score is shown during annotation time using the OVAAnnotatorConfidence class. The confidence can be used to fine tune precision/recall values. The confidence value is not normalized. Future implementations might incorporate this feature.
  
  
• New learning algorithms based on stochastic gradient descent and loss functions (Hinge loss or modified Huber loss) have been added to the system.
  
  
• Data set filters allow performing feature selection and sampling. These filters can be placed in a pipeline in the configuration file. Feature selection based on information gain has been added.
  
  
• Classifiers can be stored on existing classifier files. This allows adding trained models. If a classifier for a given category already exists, it will be overwritten with the new one.