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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.

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Last Modified: May 30, 2019   
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