Commit 2643b64d authored by Lionel's avatar Lionel

Add changelog

parent e8d70fc6
# aGrUM Changelog
## Changelog for 0.10.3
* Only bug fixes in tests
## Changelog for 0.10.2
* New method for BayesNet : minimalCondSet
* New method for all inference : evidenceImpact
* Potential has a (single) value even if no dimension.
* Bug fix for lazyPropagation
* Typos for Visual C++ compiler
* Many internal changes
## Changelog for 0.10.1
* aGrUM
* Fix GCC compilation
* ParamEstimator::setMaxThread new method
* pyAgrum
* VariableElimination and ShaferShenoy inference
* new addJointTarget and jointPosterior methods for exact inference
* pyAgrum.getPosterior now uses VariableElimination
* Fix pyAgrum.lib.notebook error for python2
* pyAgrum now linked with static library aGrUM
* pyAgrum.so (linux) size significantly reduced
## Changelog for 0.10.0
* aGrUM
* Improvements in inference : New target/evidence-driven incremental inference scheme using relevant reasoning used by Lazy/Shafer-Shenoy/Variable Elimination algorithms. Relevant reasoning leads to a major improvement of the inference (see http://www-desir.lip6.fr/~phw/aGrUM/officiel/notebooks/RelevanceReasoning.html).
* pyAgrum
* LazyPropagation API follow the new inference scheme (add/removeTarget, add/remove/chgEvidence)
installers using pip or anaconda (See https://forge.lip6.fr/projects/pyagrum/wiki/Install)
## Changelog for 0.9.3
Tag 0.9.3 has not been properly announced. Still, many changes in this release :
* Many bug fixes and API glitch/improvement
* Many internal reorganisations (compilation, test, jenkins, etc.)
* Many change in the C++ code in order to be more c++11/14
* Bug fix in learning
* Many Doxygen improvements
* Many refactors and bug fix in PRM
* Improvements
* dynamic BN in pyAgrum
* nanodbc support for pyAgrUM
* O3PRMBNReader in pyAgrum (read a prm to a BN)
* PRMExplorer in pyAgrum
* UAI reader/writer for BayesNet
* Algebra of potentials (operators on Potential)
* pyAgrum.lib.notebook refactored and simplified
* updating lrs version for credal networks
* Windows
* aGrUM/pyAgrum compilation on windows using Visual Studio 2015
## Changelog for 0.9.2
* aGrUM
* Improvements in Inference
* old LazyPropagation renamed JunctionTreeInference,
* Improved LazyPropagation ~30% faster,
* Bug fix and other improvements for relevance reasoning features.
* Improvements for Probabilistic Relational Models
* model refinements : e.g. parameterized classes, specification of CPTs using formula, etc.
* bug fixes and other improvements in dedicated inference algorithms,
* improving and fixing documentations
* new file format for Bayesian network : o3prmBNReader (reading a BN by grounding a system)
* Learning API still improved
* BNLearner templatized
* new feature for BNLearner : using a BN to specicfy variables and their modalities,
* bug fixes and improvement for parameter learning.
* other bug fixes and improvements in aGrUM architecture
* aGrUM g++5.1-ready
* etc.
* pyAgrum
* small bugs fixed and reorganisation
##Changelog for 0.9.1
* aGrUM
* Improvement in learning algorithms
* learning from databases with fewer rows than there are processors
* method to BNLearner to learn parameters from a BN's DAG
* static lib compilation for aGrUM
* bug fixes and other improvements
* pyAgrum
* Compiled for Python 3 or Python 2 (default is python3, python2 if no python3.). New option for act to choose which python : --python={2|3}.
* gumLib has moved and changed its name (in the pyAgrum package) : pyAgrum.lib
* Improving API for learning (changeLabel/parameter learning/ etc.)
* Improving graphs manipulation
* bug fixes and other improvements
## Changelog for 0.9.0
Aside from many bug fixes and general improvements such as performance optimizations in various areas, some changes are especially noteworthy:
* Functionality : Structural and parameter learning for Bayesian networks
* Model : Credal Networks, FMDP using Multi-Valued Decision Diagrams
* Language : migration to modern C++(11/14)
* Core : Improvements and optimization of basic data structures in aGrUM/core
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment