- Fixes and updates to
BayesianLogicFactors
serialization ( #92 #94 #95 #103 ) - Added new capabilities for
BayesianNetworkSampling
( #96 ) - Added possibility to use lambda functions to
RandomUtil#getRandom()
( #97 ) - Added multi query to
LoopyBeliefPropagation
( #101 ) - Restored behavior of pre 1.7.0 for
Neighborhood#random()
method ( #100 ) - Fixed an issue with
BayesianEntropy
- New documentation ( #102 )
- New logics Bayesian factors, such as
Not
,And
,Or
, andNoisyOr
( #86 ) - New ApproxLP0 algorithm ( #83 )
- Renamed
approxlp
package toapproxpl1
( #84 ) - Added new
VertexToRandomBayesian
converter ( #84 )
Extra:
- Replaced CI/CD pipeline with GitHub actions ( #84 )
- Added CITATION.cff and CITATION.bib files
- New Factor hierarchy ( #74 ). Major changes are:
- All factors are now interfaces.
- For each
factor
we can have multiple implementations. Factor
s are immutable now: the creation of a new factor is delegated to theconstructor
or to a dedicatedFactory
class.SymbolicFactor
s can now be used to keep track of operations done by algorithms.
- Added code for isipta21benchamrk ( #76 #77 )
- Removed old methods marked as
@deprecated
- Fixed an issue with sampling of
BayesianFactors
#75
- Refactoring of
Inference
andPreprocessing
hierarchies ( #66 ) - Added
Loopy Belief Propagation
algorithm ( #63 #64 #65 #67 ) - Fixed #48, an issue with
Belief Propagation
caused by wrong management of messages. - Fixed a minor issue in BeliefPropagation (introduced in 0.1.6.b)
- Added a parser for the
BIF
format ( #51 ) - Fixed #56, #62
- Minor change to
BayesianNetworkSampling
class - Updated
Sampling
algorithms ( #67 ) - Merged #70 #71
- fixed #44, #40.
- New class hierarchy for Models:
- the main interface is
Model
, - the graphical models now implements the
GraphicalModel
interface, - basic Directed Acyclic Graph is
DAGModel
, - the
BayesianNetwork
class is now a specialized case ofDAGModel
,
- the main interface is
- Added Join Tree and Belief Propagation algorithms for BayesianFactor-based models.
- Added algorithms for entropy of Bayesian and Credal networks.
- General code cleanup (mainly code style).
- Removed main methods from the library and moved to separate unit test classes.
- Updated tests and removed old experiments.
- Removed examples relative to Adaptive project.
- Updated tutorials.
- fixed #33, #32, #30.
- BayesianFactor.filter method accepts a TIntIntHashMap for specifying the states of the variables.
- EM abstract class.
- Operations for calculating the log-likelihood.
- Static method combineAll at BayesianFactor.
- Improved ObservationBuilder.
- CSV support #18.
- Bayes writer in UAI format #26.
- VCREDAL HCREDAL writers.
- VE conditionalQuery.
- Builder of a CN from a set of precise BNs.
- Common interface for inference algorithms.
- Solved bugs at renaming and sort parents.
- Bug at LP #23.
- Documentation available.
- Parsers for: V-CREDAL, BAYES and evidence.
- observation builder #20.
- Inference with EM algorithm.
- Migration of causality code to Credici.
- Parser for h-credal models in uai format.
- Polco and lpsolve made accessible from maven.
- Travis support
First published version of the software with all the code developed so far.