Added a custom exporter to convert pipeline with XGBoost models to PMML.
5.3.0
2 years ago
Added algorithmName="randomForest" attribute as part of MiningModel element for Random Forest models (PR - #56)
Added the derived fields defined in the TransformationDictionary section of the MiningModel as MiningFields within each of the Segment models for Random Forest models (PR - #57)
5.2.0
2 years ago
Added support for xgboost 1.x.x version (till 1.5.2) #53
5.1.0
2 years ago
Performance Improvement
Improved performance of xgboost exporter to a greater extend (PR - #50)
5.0.1
2 years ago
Bug fix
#39 - For LightGBM exporter
Tree node split threshold is now converted from float64 to float32 for scikit-learn's tree based models.
5.0.0
2 years ago
Major Changes
Removed customized elements from PMML schema. Now, Nyoka is completely Official PMML 4.4.1 schema compliant.
Dropped support for Keras and Retinanet exporter as these two exporters were using customized DeepNetwork element.
CICD
Usage of Travis-CI is discontinued. Instead of that Github Actions is used
4.4.0
3 years ago
Minor Update
Added support for PMML schema 4.4.1
4.3.0
3 years ago
Minor update
Added support for the latest version of scikit-learn (<=0.23.1)
Bug fix
Removed Python version constraint from setup.py. Now user can install nyoka when python version is >= 3.6
4.2.1
3 years ago
Added exporter for TrendMiner's fingerprint
This can be imported as from nyoka.custom.trendminer import FingerprintToPmml