forked from aimclub/BAMT
-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
added composite network to documentation
- Loading branch information
1 parent
a4cd82c
commit debf3bd
Showing
8 changed files
with
87 additions
and
16 deletions.
There are no files selected for viewing
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Original file line number | Diff line number | Diff line change |
---|---|---|
@@ -0,0 +1,63 @@ | ||
Composite Bayesian Networks | ||
------------------------ | ||
|
||
.. autoclass:: bamt.networks.composite_bn.CompositeBN | ||
:members: | ||
:no-undoc-members: | ||
|
||
Network initialization | ||
~~~~~~~~~~~~~~~~~~~~~~ | ||
|
||
If the dataset contains both discrete and continuous variables, ``CompositeBN`` is can be used. | ||
To initialize a ``CompositeBN`` object, you can use the following code: | ||
|
||
.. code-block:: python | ||
from bamt.networks.composite_bn import CompositeBN | ||
bn = CompositeBN() | ||
Data Preprocessing | ||
~~~~~~~~~~~~~~~~~~ | ||
|
||
Before applying any structure or parametric learning, the data should be preprocessed as follows: | ||
|
||
.. code-block:: python | ||
import bamt.Preprocessor as pp | ||
import pandas as pd | ||
from sklearn import preprocessing | ||
data = pd.read_csv("path/to/data") | ||
encoder = preprocessing.LabelEncoder() | ||
p = pp.Preprocessor([("encoder", encoder)]) | ||
preprocessed_data, _ = p.apply(data) | ||
Structure Learning | ||
~~~~~~~~~~~~~~~~~~ | ||
|
||
For structure learning of Composite BNs, ``bn.add_nodes()`` and ``bn.add_edges()`` methods are used. | ||
Data should be non-preprocessed when passed to ``bn.add_edges()`` | ||
|
||
.. code-block:: python | ||
info = p.info | ||
bn.add_nodes(info) | ||
bn.add_edges(data) # !!! non-preprocessed | ||
Parametric Learning | ||
~~~~~~~~~~~~~~~~~~~ | ||
|
||
For parametric learning of continuous BNs, ``bn.fit_parameters()`` method is used. | ||
|
||
.. code-block:: python | ||
bn.fit_parameters(data) # !!! non-preprocessed | ||
bn.get_info() |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters