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/LCM | 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 |
| JNIFIM | C/Java | Java API for Frequent Item Set Mining |
| FIMGUI | C/Java | Graphical User Interface for Frequent Item Set Mining |
| 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 |
| CoCo4R | C/R | CoCoNAD for R |
| JNICoCo | C/Java | Java API for CoCoNAD |
| 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 |
| MPR | C/Python | Best Response Regression |
| 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 |
| 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 |
| NAPa | C | Test for Neuron Assembly Participation |
| NAPaExp | C/Python | Neuron Assembly Participation: Experiments |
| 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 | C/Python | Scripts for experiments finding neuronal assemblies with the Accretion algorithm frequent item set mining |
| CoCoFIM | C/Python | Scripts for experiments finding neuronal assemblies with the CoCoNAD algorithm |
| Spectra | C/Python | Pattern Spectrum Estimation for CoCoNAD |
| HyperNAD | C/Python | Hypergraph-based Handling of Selective Participation |
| Width | C/Python | Automatic Window Width Determination for CoCoNAD |
| Overlap | C/Python | CoCoNAD with a Graded Notion of Synchrony (overlap-based support) |
| CoCoJIM | C/Python | CoCoJIM - CoCoNAD with Item Cover Similarity |
| Name | Language | Description |
|---|---|---|
| CHull | C | Convex Hull Construction |
| Pointgon | Java | Minimum Weight Triangulation of polygons with holes |
| Name | Language | Description | |
|---|---|---|---|
| SortNet | Python | Odd-even merge, pairwise and bitonic sorting networks | |
| Top-k-Net | Python | Splitter selection networks for top-k selection |
| 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 |
bcdb, with which a random database of sample cases can
be generated from a probability distribution described by a naive
or full Bayes classifier.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).
On October 23, 2014, I decided to abandon the (L)GPL licenses and adopt the MIT license for my programs, in order to avoid problems some people see with using software that is licensed under the LGPL in other software (even though the LGPL actually permits use in proprietary programs, while the GPL does not). I hope to remove these and related problems by switching to the MIT license.
The transition to the new license will be accomplished with new versions that get published. The following applies:
For any version published on or after October 23, 2014:
(MIT license, or more precisely Expat License;
to be found in the file mit-license.txt in the directory
<prgname>/doc in the source package
of the program, see also
opensource.org and
wikipedia.org)
© 1996-2024 Christian Borgelt
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
For any version published before October 23, 2014:
© 1996-2014 Christian Borgelt
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 (file copying)
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.