What's new in JProGraM 12.8
Aug 14, 2012
- A basic implementation of multilayer feedforward neural networks (ninofreno.ann package);
- Erdős-Rényi, Watts-Strogatz, and Barabási-Albert random network models (ninofreno.graph.gen package);
- Markov and higher-order exponential random graph models for networks, using k-star and k-triangle statistics (ninofreno.graph.ergm package);
- Subgraph sampling algorithms for undirected networks (random walk, random jump, snowball, inducent and incident subgraph sampler), along with methods for computing graph spectra (ninofreno.graph package);
- Area under the ROC curve calculator (ninofreno.data package);
- Lots of bugfixes and enhancements.
New in JProGraM 10.5 (May 31, 2010)
- Principal Components Analysis is now supported;
- A number of bugs within the ninofreno.gmm and ninofreno.clustering packages have veen fixed
New in JProGraM 9.1 (Jan 30, 2009)
- Principal Components Analysis is now supported;
- A number of bugs within the ninofreno.gmm and ninofreno.clustering packages have veen fixed;
- Other minor features have been added (especially within the MyMath class).
New in JProGraM 8.10 (Dec 15, 2008)
- The following algorithms are now supported by JProGraM:
- K-Means (for clustering);
- Kaufman-Rousseuw algorithm for initializing cluster centroids;
- Gaussian Mixture Model for probability density function estimation.
New in JProGraM 8.6 (Sep 2, 2008)
- The following statistical models are now supported by JProGraM:
- Parzen Windows for probability density function estimation;
- Probabilistic decision trees for discrete pattern classification;
- Dependency networks for discrete pseudo-likelihood estimation.