Christian Borgelt's Web Pages

A toolbox combining several intelligent data analysis programs under a uniform graphical user interface.

If you are looking for a frequent item set mining and/or association rule induction program and you are unsure which one to choose, it is recommended to use either Eclat or FPgrowth.

Name | Language | Description |
---|---|---|

FIMGUI | Java | Frequent Item Set Mining GUI and Viewer |

ARuleGUI | Java | Association Rule Mining GUI and Viewer |

Apriori | C | Frequent Item Set Mining
(all, closed, maximal, generators) and Association Rule Induction |

Eclat | C/Python | Frequent Item Set Mining
(all, closed, maximal, generators) and Association Rule Induction |

FPgrowth | C | Frequent Item Set Mining
(all, closed, maximal, generators) and Association Rule Induction |

RElim | C | Frequent Item Set Mining (all, closed, maximal, generators, fault-tolerant) |

SaM | C | Frequent Item Set Mining (all, closed, maximal, generators, fault-tolerant) |

SODIM | C | Frequent Item Set Mining (fault-tolerant) |

IsTa | C | Frequent Item Set Mining (closed and maximal) |

Carpenter | C | Frequent Item Set Mining (closed and maximal) |

PyFIM | C/Python | Frequent Item Set Mining for Python |

JIM | C | Jaccard Item Set Mining / Cover Similarity |

CoCoNAD | C | Continuous-time Closed Neuron Assembly Detection Frequent Pattern Mining in Point Processes |

PyCoCo | C/Python | CoCoNAD for Python |

CoCoGUI | C/Java | Graphical User Interface for CoCoNAD + PSF + PSR |

Seqwog | C | Frequent Sequence Mining |

Sequoia | C | Frequent Sequence Mining |

MoSS | Java | Molecular Substructure Miner |

(other than frequent pattern mining)

Name | Language | Description |
---|---|---|

FrIDA | C | Free Intelligent Data Analysis Toolbox |

MPR | C | Multivariate Polynomial Regression |

RegGUI | Java | Multivariate Polynomial Regression GUI and Viewer |

Dtree | C | Decision and Regression Tree Induction |

DTreeGUI | Java | Decision and Regression Tree GUI and Viewer |

Bayes | C | Naive and Full Bayes Classifier Induction |

BayesGUI | Java | Bayes Classifier GUI |

BCView | C | Bayes Classifier Visualization |

NPoss | C | Naive Possibilistic Classifier Induction |

INeS | C | Induction of Network Structures (Graphical Models) |

MLP | C | Multilayer Perceptron |

MLPGUI | Java | Multilayer Perceptron GUI |

LVQ | C | Learning Vector Quantization |

RBF | C | Radial Basis Function Network Training |

RBFGUI | Java | Radial Basis Function Network Training GUI |

Cluster | C | Fuzzy and Probabilistic Clustering |

ClusterGUI | Java | Fuzzy and Probabilistic Clustering GUI |

PtLess | C | Prototype-Less Fuzzy Clustering |

Table | C | Table Utilities |

Viewers | Java | Simple Viewers for Tabular Data |

Matrix | C | Matrix Utilities |

Hubness | C | Analysis of the Hubness Phenomenon |

Name | Language | Description |
---|---|---|

GenPST | C | Generate Parallel Spike Trains |

NAss | C | Finding Neurons Participating in Assemblies |

Accretion | C | Finding Neuronal Assemblies |

Surrogates | Python | Surrogate Generation for the Analysis of Parallel Spike Trains |

CoCoNAD | C | Continuous-time Closed Neuron Assembly Detection / Frequent Pattern Mining in Point Processes |

PyCoCo | C | CoCoNAD for Python |

CoCoGUI | C/Java | Graphical User Interface for CoCoNAD + PSF + PSR |

AccFIM | Python | Scripts for experiments finding neuronal assemblies with the Accretion algorithm frequent item set mining |

CoCoFIM | Python | Scripts for experiments finding neuronal assemblies with the CoCoNAD algorithm |

Name | Language | Description |
---|---|---|

CHull | C | Convex Hull Construction |

Pointgon | Java | Minimum Weight Triangulation of polygons with holes |

Name | Language | Description |
---|---|---|

MLP Demo | C | Multilayer Perceptron Demonstration |

LVQ Demo | C | Learning Vector Quantization Demonstration |

SOM Demo | C | Self-Organizing Map Demonstration |

Hopfield Demo | C | Hopfield Network Demonstration |

PSOpt Demo | Java | Particle Swarm Optimization Demonstration |

ACOpt Demo | Java | Ant Colony Optimization Demonstration |

Name | Language | Description |
---|---|---|

Hamster | C | Programming Contest Environment |

Bridgit | C | Simple Two Player Game |

Sudoku | C | Simple Sudoku Puzzle Solver |

- The bayes package contains the program
`bcdb`, with which a random database of sample cases can be generated from a probability distribution described by a naive or full Bayes classifier. - The ines package contains the program
`gendb`, with which a random database of sample cases can be generated from a probability distribution described by a Bayesian network (over attributes with finite domains).

All programs are free software; you can redistribute them
and/or modify them under the terms of the
GNU General Public License or the
GNU Lesser (Library) General Public License
as published by the
Free Software Foundation.
Which license applies depends on the program.
Check the copyright notice in the directory
*<prgname>*`/doc`
in the source package of the program to find out.

All programs are distributed in the hope that they will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License or the GNU Lesser (Library) General Public License for more details.