# rf-debugger

**Repository Path**: mirrors_vruusmann/rf-debugger

## Basic Information

- **Project Name**: rf-debugger
- **Description**: A command-line application for the "deep analysis" of Random Forest models
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-09-26
- **Last Updated**: 2026-04-26

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

A toy project that demonstrates the use of JPMML-Model and JPMML-Evaluator APIs to "deep analyze" the predictions of Random Forest models.

# Prerequisites #

* Java 1.7 or newer

# Installation #

Enter the project root directory and build using [Apache Maven] (http://maven.apache.org/):

```
mvn clean package
```

The build produces an executable uber-JAR file `target/rf-debugger-executable-1.0-SNAPSHOT.jar`, which contains an executable application class `org.jpmml.example.RfDebugger`.

# Usage #

Debugging a Random Forest PMML file that has been produced by R:

```
java -cp target/rf-debugger-executable-1.0-SNAPSHOT.jar org.jpmml.example.RfDebugger src/etc/R/RandomForestIris.pmml src/etc/R/Iris.csv
```

Debugging a Random Forest PMML file that has been produced by Python (Scikit-Learn):

```
java -cp target/rf-debugger-executable-1.0-SNAPSHOT.jar org.jpmml.example.RfDebugger src/etc/scikit-learn/RandomForestIris.pmml src/etc/scikit-learn/Iris.csv
```