v2.1.0

B-Analytics · Nov 2, 2024 · f7f1311 · f7f1311
1 parent 84d7c88
commit f7f1311
Show file tree

Hide file tree

Showing 6 changed files with 26 additions and 65 deletions.
diff --git a/Makefile b/Makefile
diff --git a/README.md b/README.md
@@ -31,10 +31,10 @@ yhat_dipls, err = m.predict(X_test, y_test=[])
 
 ## How to apply mdi-PLS
 ```python
-from diPLSlib.models import DIPLS as dipls
+from diPLSlib.models import DIPLS
 
 # Training
-m = dipls(X, y, X_source, X_target, 2)
+m = DIPLS(X, y, X_source, X_target, 2)
 l = [100000] #  Regularization
 m.fit(l, target_domain=2)
 
@@ -48,10 +48,10 @@ yhat_dipls, err = m.predict(X_test, y_test=[])
 
 ## How to apply GCT-PLS
 ```python
-from diPLSlib.models import GCTPLS as gctpls
+from diPLSlib.models import GCTPLS
 
 # Training
-m = gctpls(X, y, X_source, X_target, 2)
+m = GCTPLS(X, y, X_source, X_target, 2)
 l = [100] #  Regularization
 m.fit(l)
 

diff --git a/changelog.md b/changelog.md
@@ -61,6 +61,22 @@ All notable changes to this project will be documented in this file.
 
 [2.0.0]: https://github.com/B-Analytics/di-PLS/releases/tag/v2.0.0
 
+## [2.1.0] - 2024-11-02
+### Added
+- utils submodule added to outsource utility functions.
+- Documentation added
+
+### Changed
+- N/A
+
+### Fixed
+- N/A
+
+### Removed
+- N/A
+
+[2.1.0]: https://github.com/B-Analytics/di-PLS/releases/tag/v2.1.0
+
 
 
 

diff --git a/diPLSlib.egg-info/PKG-INFO b/diPLSlib.egg-info/PKG-INFO
@@ -1,6 +1,6 @@
 Metadata-Version: 2.1
 Name: diPLSlib
-Version: 2.0.0
+Version: 2.1.0
 Summary: Python package for domain adaptation in multivariate regression
 Home-page: https://github.com/B-Analytics/di-PLS
 Author: Ramin Nikzad-Langerodi
@@ -48,10 +48,10 @@ yhat_dipls, err = m.predict(X_test, y_test=[])
 
 ## How to apply mdi-PLS
 ```python
-from diPLSlib.models import DIPLS as dipls
+from diPLSlib.models import DIPLS
 
 # Training
-m = dipls(X, y, X_source, X_target, 2)
+m = DIPLS(X, y, X_source, X_target, 2)
 l = [100000] #  Regularization
 m.fit(l, target_domain=2)
 
@@ -65,10 +65,10 @@ yhat_dipls, err = m.predict(X_test, y_test=[])
 
 ## How to apply GCT-PLS
 ```python
-from diPLSlib.models import GCTPLS as gctpls
+from diPLSlib.models import GCTPLS
 
 # Training
-m = gctpls(X, y, X_source, X_target, 2)
+m = GCTPLS(X, y, X_source, X_target, 2)
 l = [100] #  Regularization
 m.fit(l)
 

diff --git a/make.bat b/make.bat
diff --git a/setup.py b/setup.py
@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="diPLSlib",
-    version="2.0.0",
+    version="2.1.0",
     author="Ramin Nikzad-Langerodi",
     author_email="[email protected]",
     description="Python package for domain adaptation in multivariate regression",