Annif 0.45
This release includes a new omikuji backend to support tree-based extreme multilabel classification machine learning algorithms, which give a big improvement to the quality of the subject indexing results. The --backend-param/-p option is introduced to the CLI train and learn commands (previously that option was only available for suggest and eval); the option can be used to override the parameters from the config file. Also Python 3.8 support is introduced - however, the nn_ensemble backend requires TensorFlow 2.0, which is not yet available for Python 3.8. The Vowpal Wabbit ensemble backend has been removed, as the neural network ensemble has similar features and gives better results.
New features:
- #343/#366/#368/#371 Omikuji backend
- #250/#289 Support backend param option in train and learn commands
- #345/#370 Support for Python 3.8
Bug fixes:
Improvements/Maintenance: