document supported versions of packages

README.md

@@ -48,6 +48,9 @@ pip install m2cgen
 | **Random Forest** | <ul><li>ExtraTreesClassifier</li><li>LGBMClassifier(rf booster only)</li><li>RandomForestClassifier</li><li>XGBRFClassifier(binary only, multiclass is not supported yet)</li></ul> | <ul><li>ExtraTreesRegressor</li><li>LGBMRegressor(rf booster only)</li><li>RandomForestRegressor</li><li>XGBRFRegressor</li></ul> |
 | **Boosting** | <ul><li>LGBMClassifier(gbdt/dart/goss booster only)</li><li>XGBClassifier(gbtree/gblinear booster only)</li><ul> | <ul><li>LGBMRegressor(gbdt/dart/goss booster only)</li><li>XGBRegressor(gbtree/gblinear booster only)</li></ul> |
 
+You can find versions of packages with which compatibility is guaranteed by CI tests [here](https://github.com/BayesWitnesses/m2cgen/blob/master/requirements-test.txt#L1).
+Other versions can also be supported but they are untested.
+
 ## Classification Output
 ### Linear / Linear SVM / Kernel SVM
 #### Binary

requirements-test.txt

@@ -1,13 +1,18 @@
-numpy==1.18.2
-scipy==1.4.1
+# Supported models
 scikit-learn==0.22.2.post1
 xgboost==1.0.2
 lightgbm==2.3.1
+statsmodels==0.11.1
+git+git://github.com/scikit-learn-contrib/lightning.git@b96f9c674968496e854078163c8814049a7b9f43
+
+# Testing tools
 flake8==3.7.9
 pytest==5.4.1
 pytest-mock==3.0.0
 coveralls==2.0.0
 pytest-cov==2.8.1
+
+# Other stuff
+numpy==1.18.2
+scipy==1.4.1
 py-mini-racer==0.2.0
-statsmodels==0.11.1
-git+git://github.com/scikit-learn-contrib/lightning.git@b96f9c674968496e854078163c8814049a7b9f43