Full Changelog: 0.6.0...0.7.0
- MajorFeature: Add
empulse.models.CSTreeClassifier
,empulse.models.CSForestClassifier
,
andempulse.models.CSBaggingClassifier
to support cost-sensitive decision tree and ensemble models - Enhancement: Add support for scikit-learn 1.5.2 (previously Empulse only supported scikit-learn 1.6.0 and above).
- API: Removed the
emp_score
andemp
functions from theempulse.metrics
module.
Use theempulse.metrics.Metric
class instead to define custom expected maximum profit measures.
For more information, read the User Guide. - API: Removed numba as a dependency for Empulse. This will reduce the installation time and the size of the package.
- Fix: Fix
empulse.metrics.Metric
when defining stochastic variable with fixed values. - Fix: Fix
empulse.metrics.Metric
when stochastic variable has infinite bounds. - Fix: Fix
empulse.models.CSThresholdClassifier
when costs of predicting positive and negative classes are equal. - Fix: Fix documentation linking issues to sklearn