Updated docs and Bumpde to 2.1.9.

SekouD · Jun 20, 2018 · f423891 · f423891
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diff --git a/HISTORY.rst b/HISTORY.rst
@@ -2,6 +2,22 @@
 History
 =======
 
+2.1.9 (2018-06-21)
+------------------
+
+* Now the Conjugator adds additional information to the Verb object returned.
+    - If the verb under consideration is already in Verbiste, the conjugation for the verb is retrieved directly from memory.
+    - If the verb under consideration is unknown in Verbiste, the Conjugator class now sets the boolean attribute 'predicted' and the float attribute confidence score to the instance of the Verb object the Conjugator.conjugate(verb) returns.
+* Added `Type annotations`_ to the whole library for robustness and ease of scaling-out
+* The performance of the Engish and Romanian Models have improved significantly lately. I guess in a few more iteration they will be on par with the French Model which is the best performing at the moment as i have been tuning its parameters for a caouple of year now. Not so much with the other languages, but if you update regularly you will see nice improvents in the 2.2 release.
+* Enhanced the localization of the program.
+* Now the user interface of mlconjug is avalaible in French, Spanish, Italian, Portuguese and Romanian, in addition to English.
+* `All the documentation of the project`_ have been translated in the supported languages.
+
+
+.. _Type annotations: https://github.com/python/typeshed
+.. _All the documentation of the project: https://mlconjug.readthedocs.io/en/latest/
+
 
 2.1.5 (2018-06-15)
 ------------------

diff --git a/README.rst b/README.rst
@@ -39,9 +39,11 @@ MLConjug
 - a classifier using Stochastic Gradient Descent.
 
 | MLConjug uses scikit-learn to implement the Machine Learning algorithms.
-| Users of the library can use any compatible classifiers from scikit-learn to modify and retrain the model.
+| Users of the library can use any compatible classifiers from scikit-learn to modify and retrain the models.
 
-The training data is based on Verbiste https://perso.b2b2c.ca/~sarrazip/dev/verbiste.html .
+| The training data for the french model is based on Verbiste https://perso.b2b2c.ca/~sarrazip/dev/verbiste.html .
+| The training data for English, Spanish, Italian, Portuguese and Romanian was generated using unsupervised learning techniques
+| using the French model as a model to query during the trainig.
 
 
 * Free software: MIT license

diff --git a/mlconjug/__init__.py b/mlconjug/__init__.py
@@ -26,7 +26,7 @@
 
 __author__ = """SekouD"""
 __email__ = 'sekoud.python@gmail.com'
-__version__ = '2.1.8'
+__version__ = '2.1.9'
 __copyright__ = "Copyright (c) 2017, SekouD"
 __credits__ = ("Pierre Sarrazin",)
 __license__ = "MIT"

diff --git a/setup.cfg b/setup.cfg
@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 2.1.8
+current_version = 2.1.9
 commit = True
 tag = True
 

diff --git a/setup.py b/setup.py
@@ -38,7 +38,7 @@
 
 setup(
     name='mlconjug',
-    version='2.1.8',
+    version='2.1.9',
     description="A Python library to conjugate French, English, Spanish, Italian, Portuguese and Romanian verbs using Machine Learning techniques.",
     long_description=readme + '\n\n' + installation + '\n\n' + history,
     author="SekouD",