v0.5: Release notes and Version number

JIRA: MADLIB-700, 715
Updated release notes for MADLIB v0.5 release and updated the
version number.

ReleaseNotes.txt

@@ -9,6 +9,64 @@ commit history located at https://github.com/madlib/madlib/commits/master.
 
 Current list of bugs and issues can be found at http://jira.madlib.net.
 
+--------------------------------------------------------------------------------
+MADlib v0.5
+
+Release Date: 2012-Nov-15
+
+Bug Fixes:
+* K-means:
+    - Improved handling of invalid arguments (MADLIB-359, 361)
+* Sketch-based estimators:
+	  - Addressed security vulnerability (MADLIB-630)
+
+New Features / Improvements:
+* Association Rules (Apriori):
+    - Improved reporting output format for better usability (MADLIB-411)
+	  - Significant improvement in performance (MADLIB-638)
+* C++ (Database) Abstraction Layer:
+    - Extension to support modular transition states (MADLIB-499)
+    - Extension to support functions returning set of values (MADLIB-638)
+* Conditional Random fields:
+    - Support for Linear Chain Conditional Random Fields for NLP (MADLIB-628)
+* Decision Tree:
+    - Improved performance for C4.5 and Random forests (MADLIB-605)
+    - Improved encoding (MADLIB-590)
+* Infrastructure:
+    - Convex optimization framework
+* K-means:
+    - Code refactoring and Improved performance
+      (MADLIB-454, MADLIB-522, MADLIB-678)
+    - Silhouette function for k-means (MADLIB-681)
+* Low-rank Matrix Factorization
+    - New module
+* Logistic Regression:
+    - Support for Multinomial Logistic Regression (MADLIB-575)
+* Naive Bayes
+    - Significant improvement in performance (MADLIB-611, 619, 626)
+* Regression Analysis:
+    - Support for Cox Proportional Hazards test (MADLIB-576)
+* Sampling
+    - Added weighted sampling of a single row (MADLIB-584)
+* SVD Matrix Factorization:
+    - Improved performance (MADLIB-578)
+
+Documentation:
+* Conditional Random Fields:
+    - Example added for CRF module (MADLIB-731)
+* SVD Matrix Factorization:
+    - Incremental-gradient SVD algorithm (MADLIB-572)
+
+Known issues:
+* Multinomial Logistic Regression:
+    - Number of independent variables cannot exceed 65535 (MADLIB-665)
+* Naive Bayes:
+    - Current implementation of Naive Bayes is only suitable for
+        categorical attributes (MADLIB-679)
+    - NULL input values not accepted for attributes (MADLIB-614)
+    - NULL probabilities given for test set values not seen in
+      training set (MADLIB-523)
+
 --------------------------------------------------------------------------------
 MADlib v0.4.1
 

src/config/Version.yml

@@ -1 +1 @@
-version: 0.4.1
+version: 0.5