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Some unnecessary stuff removed. Documentation update.
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Diff for: ‎README.md

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@@ -34,7 +34,7 @@ The JAR file will be placed in *adaa.analytics.rules/build/libs* subdirectory. O
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```
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java -jar rulekit-<version>-all.jar minimal-deals.xml
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```
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Ignore the SLF4J warning reported on the console - it does not affect the procedure. The results of the analysis will be located in *./examples/results-minimal/deals/* folder. Note, that the repository already contains reference results - they will be overwritten. See [this Wiki section](../../wiki/1-Batch-interface) for detailed information on how to configure batch analyses in RuleKit.
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Ignore the SLF4J warning reported on the console - it does not affect the procedure. The results of the analysis will be located in *./examples/results-minimal/deals/* folder. Note, that the repository already contains reference results - they will be overwritten. See [this Wiki section](https://github.com/adaa-polsl/RuleKit/wiki/1-Batch-interface) for detailed information on how to configure batch analyses in RuleKit.
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## RapidMiner plugin
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As the next step, please import [./examples/regression.rmp](./examples/regression.rmp) process. After executing it, datasets are loaded from the RM repository with *Retrieve* operators. Then, the training set is provided as an input for *RuleKit Generator*. The model generated by *RuleKit Generator* is then applied on unseen data (*Apply Model* operator). The performance of the prediction is assesed using *RuleKit Evaluator* operator. Performance metrices as well as generated model are passed as process outputs.
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See [this Wiki section](../../wiki/2-RapidMiner-plugin) for detailed information how to configure RuleKit RapidMiner plugin.
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See [this Wiki section](https://github.com/adaa-polsl/RuleKit/wiki/2-RapidMiner-plugin) for detailed information how to configure RuleKit RapidMiner plugin.
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## R package
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Below we present a survival analysis of *BMT-Ch* dataset with RuleKit R package. The set concerns the problem of analyzing factors contributing to the patients’ survival following bone marrow transplants. In order to perform the experiment, please run [./examples/survival.R](./examples/survival.R) script in R. As a result, a rule model is trained and survival function estimates for the entire dataset and for the rules are plotted.
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[This Wiki section](../../wiki/3-R-package) contains detailed information on using RuleKit R package.
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[This Wiki section](https://github.com/adaa-polsl/RuleKit/wiki/3-R-package) contains detailed information on using RuleKit R package.
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## Python package
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Rulekit Python package can be found [here](https://github.com/adaa-polsl/RuleKit-python)
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# Documentation
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The detailed RuleKit documentation can be found on [Wiki pages](../../wiki) which cover the following topics:
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1. [Batch interface](../../wiki/1-Batch-interface)
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1. [General information](../../wiki/1-Batch-interface#11-general-information)
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2. [Parameter set definition](../../wiki/1-Batch-interface#12-parameter-set-definition)
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3. [Dataset definition](../../wiki/1-Batch-interface#13-dataset-definition)
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4. [Example](../../wiki/1-Batch-interface#14-example)
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2. [RapidMiner plugin](../../wiki/2-RapidMiner-plugin)
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1. [Installation](../../wiki/2-RapidMiner-plugin#21-installation)
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2. [Usage](../../wiki/2-RapidMiner-plugin#22-usage)
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3. [Example](../../wiki/2-RapidMiner-plugin#23-example)
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3. [R package](../../wiki/3-R-package)
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1. [Installation](../../wiki/3-R-package#31-installation)
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2. [Usage](../../wiki/3-R-package#32-usage)
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3. [Example](../../wiki/3-R-package#33-example)
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4. [Quality and evaluation](../../wiki/4-Quality-and-evaluation)
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1. [Rule quality](../../wiki/4-Quality-and-evaluation#41-rule-quality)
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2. [Model characteristics](../../wiki/4-Quality-and-evaluation#42-model-characteristics)
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2. [Performance metrices](../../wiki/4-Quality-and-evaluation#43-performance-metrices)
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5. [Output files](../../wiki/5-Output-files)
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1. [Training report](../../wiki/5-Output-files#51-training-report)
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2. [Prediction performance report](../../wiki/5-Output-files#52-prediction-performance-report)
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6. [User-guided induction](../../wiki/6-User-guided-induction)
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1. [Defining user's knowledge](../../wiki/6-User-guided-induction#61-defining-users-knowledge)
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2. [Examples from GuideR paper](../../wiki/6-User-guided-induction#62-examples-from-guider-paper)
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7. [Library API](../../wiki/7-Library-API)
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1. [Running an experiment](../../wiki/7-Library-API#71-running-an-experiment)
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2. [Developing a new algorithm](../../wiki/7-Library-API#72-developing-a-new-algorithm)
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8. [Empirical results](../../wiki/8-Empirical-results)
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9. [Contrast set mining](../../wiki/9-Contrast-set-mining)
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The detailed RuleKit documentation can be found on [Wiki pages](https://github.com/adaa-polsl/RuleKit/wiki) which cover the following topics:
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1. [Batch interface](https://github.com/adaa-polsl/RuleKit/wiki/1-Batch-interface)
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1. [General information](https://github.com/adaa-polsl/RuleKit/wiki/1-Batch-interface#11-general-information)
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2. [Parameter set definition](https://github.com/adaa-polsl/RuleKit/wiki/1-Batch-interface#12-parameter-set-definition)
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3. [Dataset definition](https://github.com/adaa-polsl/RuleKit/wiki/1-Batch-interface#13-dataset-definition)
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4. [Example](https://github.com/adaa-polsl/RuleKit/wiki/1-Batch-interface#14-example)
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2. [RapidMiner plugin](https://github.com/adaa-polsl/RuleKit/wiki/2-RapidMiner-plugin)
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1. [Installation](https://github.com/adaa-polsl/RuleKit/wiki/2-RapidMiner-plugin#21-installation)
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2. [Usage](https://github.com/adaa-polsl/RuleKit/wiki/2-RapidMiner-plugin#22-usage)
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3. [Example](https://github.com/adaa-polsl/RuleKit/wiki/2-RapidMiner-plugin#23-example)
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3. [R package](https://github.com/adaa-polsl/RuleKit/wiki/3-R-package)
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1. [Installation](https://github.com/adaa-polsl/RuleKit/wiki/3-R-package#31-installation)
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2. [Usage](https://github.com/adaa-polsl/RuleKit/wiki/3-R-package#32-usage)
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3. [Example](https://github.com/adaa-polsl/RuleKit/wiki/3-R-package#33-example)
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4. [Quality and evaluation](https://github.com/adaa-polsl/RuleKit/wiki/4-Quality-and-evaluation)
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1. [Rule quality](https://github.com/adaa-polsl/RuleKit/wiki/4-Quality-and-evaluation#41-rule-quality)
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2. [Model characteristics](https://github.com/adaa-polsl/RuleKit/wiki/4-Quality-and-evaluation#42-model-characteristics)
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2. [Performance metrices](https://github.com/adaa-polsl/RuleKit/wiki/4-Quality-and-evaluation#43-performance-metrices)
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5. [Output files](https://github.com/adaa-polsl/RuleKit/wiki/5-Output-files)
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1. [Training report](https://github.com/adaa-polsl/RuleKit/wiki/5-Output-files#51-training-report)
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2. [Prediction performance report](https://github.com/adaa-polsl/RuleKit/wiki/5-Output-files#52-prediction-performance-report)
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6. [User-guided induction](https://github.com/adaa-polsl/RuleKit/wiki/6-User-guided-induction)
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1. [Defining user's knowledge](https://github.com/adaa-polsl/RuleKit/wiki/6-User-guided-induction#61-defining-users-knowledge)
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2. [Examples from GuideR paper](https://github.com/adaa-polsl/RuleKit/wiki/6-User-guided-induction#62-examples-from-guider-paper)
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7. [Library API](https://github.com/adaa-polsl/RuleKit/wiki/7-Library-API)
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1. [Running an experiment](https://github.com/adaa-polsl/RuleKit/wiki/7-Library-API#71-running-an-experiment)
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2. [Developing a new algorithm](https://github.com/adaa-polsl/RuleKit/wiki/7-Library-API#72-developing-a-new-algorithm)
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8. [Empirical results](https://github.com/adaa-polsl/RuleKit/wiki/8-Empirical-results)
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9. [Contrast set mining](https://github.com/adaa-polsl/RuleKit/wiki/9-Contrast-set-mining)
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JavaDoc for the project is available [here](https://adaa-polsl.github.io/RuleKit/).
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Diff for: ‎adaa.analytics.rules/build.gradle

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}
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sourceCompatibility = 1.8
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version = '1.7.0'
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version = '1.7.1'
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jar {

Diff for: ‎adaa.analytics.rules/src/main/java/adaa/analytics/rules/consoles/RSupportedConsole.java

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