0.10.2

Fix for bug #105

v0.10.1

Fix for bug "DBN" not in config found.

0.10.0

The impute functionality has been extended with the MICE method thanks to @Ananyapam7 (issue #81).
In addition, I also added functionality to impute missing categorical values.

Key features include:

• Supports K-NN imputation for numeric columns.
• Supports MICE imputation for numeric columns.
• Numeric columns are auto-identified and converted for imputation where necessary.
• Includes options to specify the imputation estimator, number of iterations (max_iter), and verbosity level for logging.
• String/categorical columns are imputed.

Created a new file impute.py for imputation related functions.
See examples and more information in the documentation pages.

0.9.1

• bug fix when using parameter learning

0.9.0

• Lingam methods (Direct and ICA) are implemented to model datasets with continuous variables (without discretizing). See docs here. #36 #94
• Plotting is now possible using Graphviz which creates more clear figures. See docs here.
• For Constraint-based (PC), CII 9 tests are included and the alpha can be set.
• Parameter showfig and visible is available now for plotting #103
• Dynamic Bayesian Network (DBN) implemented. #100. See docs here and here.
• Impute functionality implemented in case of missing values. #81 See docs over here.
• Updated docstrings and sphinx documentation pages.
• Created a logo! :-)

v0.8.9

• Fix for issue #98 Where the interactive plot sometimes produced an error. The issue was that nodenames are cleaned in d3blocks but this step was skipped in the interactive plot of bnlearn.

0.8.8

• Latest version of pandas is supported again.

0.8.7

• Fix for showing the weights in the edges for the static plot

0.8.6

• Fix for issue #99
• Removed d3blocks from setup /requirements and added it as check when using the interactive plot functionality

0.8.5

• add d3blocks to setup and requirements with minimum version. The wrong version can break the interactive plots.