All notable changes to this project will be documented in this file.
The format is based on Keep a Changelog, and this project adheres to Semantic Versioning.
- MaxEntropyBinarizer also uses stricter test to detect binary features
- PSL uses stricter test to detect binary features
- PSL classifier
- probability predictions can return confidence intervals
- probability calibration using BetaCalibration
- stages can now be sliced and iterated (_getitem_(), _iter_())
- Metrics
- Weighted loss metric
- Rank loss metric
- PSL more robust against non-standard class labels like "True"/"False" instead of boolean values
- PSL supports Dataframes as inputs
- PSL supports instance weights
- Extended precision at recall function
- Significantly extended the configuration capabilities with predefined features to limit the PSLs searchspace
- PSL global loss defaults to sum(cascade)
- rewrote/extracted expected entropy calculation
- PSL inspect is now more robust
- PSL classifier optimization regarding global loss was incorrect
- _ClassifierAtK
- Sigmoid calibration additional to isotonic
- PSL classifier
- Make optimization loss configurable
- Small
searchspace_analyisis(·)function makes lookahead choice more informed
- Fixed lookahead search space and considering global loss for model-sequence evaluation
- Updated dependencies and added black
- Moved Binarizer to different module
- Moved PSL hyperparameters to constructor
- _ClassifierAtK
- Expected entropy for stage 0 now also calculated wrt. base 2
- Data with only 0 or 1 is now also interpret as binary data
- Small import error
- Add brute force threshold optimization method to find the global optimum, bisect optimizer remains default method
- Restructured source files
- PSL is now correctly handles when all instances belong to the negative class
- #1 if the first feature is assigned a negative score, it is now assigned the most negative score
- PSL classifier can now run with continuous data and optimally (wrt. expected entropy) select thresholds to binarize the data
- Significantly improved optimum calculation for MinEntropyBinarizer (the same optimization algorithm is shared with the psls internal binarization algorithm)
- PSL classifier
- introduced parallelization
- implemented l-step lookahead
- simple inspect(·) method that creates a tabular representation of the model
- Initial implementation of the PSL algorithm