https://github.com/samthiriot/knime.bayesiannetworks

Bayesian Networks nodes for KNIME
https://github.com/samthiriot/knime.bayesiannetworks

bayesian-networks knime knime-node scientific-computing scientific-machine-learning scientific-workflows synthetic-data synthetic-dataset-generation synthetic-population-library synthetic-populations

Last synced: 2 months ago
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Bayesian Networks nodes for KNIME

• Host: GitHub
• URL: https://github.com/samthiriot/knime.bayesiannetworks
• Owner: samthiriot
• Created: 2020-08-04T15:37:15.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2022-04-07T08:57:03.000Z (over 3 years ago)
• Last Synced: 2025-06-02T06:28:02.993Z (4 months ago)
• Topics: bayesian-networks, knime, knime-node, scientific-computing, scientific-machine-learning, scientific-workflows, synthetic-data, synthetic-dataset-generation, synthetic-population-library, synthetic-populations
• Language: Java
• Homepage:
• Size: 1.33 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 25
• Metadata Files:
  • Readme: README.md

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README

          
# knime.bayesiannetworks

Bayesian Networks nodes for KNIME.

Enables the generation of synthetic datasets, generation of synthetic populations, learning of statistical models, statistical inference. 

## Features

Adds nodes for the KNIME workflow engine to use Bayesian networks.

* read Bayesian networks (from the XMLBIF format)

* write Bayesian networks (in XMLBIF, BIF and net formats)

* sample data from a Bayesian network: create n entities compliant with the distribution of probabilities described by the network

* complete existing data tables by addings new columns and the probability from the network

* add nodes to a Bayesian network from KNIME data tables

* enumerate all the combinations of values and the corresponding probabilities

* compute the probability of a row

* measure the difference between two Bayesian networks having the same structure

# install it

The easiest way to install the plugin is to use the update site I publish in https://knime.res-ear.ch 

Using KNIME version 4.2 or above, go to menu Help/Install new software. 

Click the "Add..." button and add repository:

   Name: samthiriot KNIME nodes

   https://knime.res-ear.ch

Then select "Bayesian Networks for KNIME", and follow the usual process. 

# Use it

## Read, Sample, Measure

A basic case is to read an existing Bayesian network from a file and to sample entities (generate KNIME rows).

To measure the quality of the sampling, one learns the probabilities of the Bayesian network and compare them with the reference network.

![example of workflow with reading, sampling and measure of quality](./doc/screenshot_read_sample_measure.png)

You can [download it](./doc/example_read_sample_measure.knwf) to try it yourself.

## Create, Sample, Write

The Bayesian network can be easily created in KNIME. 

In this example ([download it](./doc/example_create_sample_write.knwf)), we show:

* how to read a table from a CSV file, and use it as the Conditional Probability Table of a new variable in the Bayesian network

* how to create a table by hand in KNIME, and use it as a Conditional Probability Table of a new variable,

* how to aggregate statistics from a KNIME table by using a standard "group by" node, then insert it as a Bayesian network 

Then the Bayesian network can be used for sampling or data augmentation, and can be written in standard format.

![example of workflow creation, sampling and writing](./doc/screenshot_create_sample_write.png)

## Data fusion 

The Bayesian network can be used to "augment" or join data.

In this example ([download it](./doc/example_augment_data.knwf)), we show:

* we read existing data having only two columns `surface` and `annee` 

* the missing column is present in the Bayesian network which describes `p( combustible | surface, annee )`

* for every row, the node samples missing data according to the probabities `p( combustible | surface, annee )` and existing values `surface` and `annee` in the row. 

![example of data fusion](./doc/screenshot_augment_data.png)

# developers' corner 

## set up development environment 

* set up a development environment for a KNIME plugin as ![in the KNIME documentation](https://docs.knime.com/latest/analytics_platform_new_node_quickstart_guide/index.html#_introduction). This involves to ![set up the KNIME SDK](https://github.com/knime/knime-sdk-setup)

* clone this repository, then import it as Java projects into Eclipse

* download jar dependancies: run the "maven copy dependancies into lib.launch"

test the code without KNIME:

* directory "test", run as... JUnit. This should heat your CPU a bit but should end with green lights (timeouts are acceptable as they depend on the test cases and your configuration). Solve dependancy issues.

test the plugin inside KNIME:

* right click on knime-sdk-setup, run as... run configurations... KNIME Analytics

* the "Bayesian Networks" logo should be part of the splash screen

* the "Bayesian networks" section should be visible in the "community" family

* create a new KNIME workflow 

## frequent questions

Par of dependancies are managed by Maven. Yet they are packaged as libs in the plugin:

* maven dependancies are in pom.xml

* refresh the maven dependancies

* then run the "copy maven dependancies into lib"

* then ensure all these libs are both in the plugin.xml imports but also in the build path 

## export the plugin

See https://github.com/samthiriot/knime.updatesite