• Increase font size
  • Default font size
  • Decrease font size
DTAI ML Systems Machine Learning systems

Machine Learning systems

This is the list of our available machine learning software

  • ACE (A Combined Engine): is the relational datamining system that implements a.o. the algorithms Tilde, Warmr, ICL, and RRL.
  • BiQL a system for analyzing information networks.
  • Clus: a decision tree and rule induction system that implements the predictive clustering framework.
  • CP4IM: a system for mining frequent itemsets using constraint programming.
  • C-FARMR: a system for mining free clauses.
  • DL8(.tar.gz): a constraint-based optimal decision tree learner.
  • DMax Chemistry Assistant a QSAR data mining system.
  • Experiment database: a database designed to store learning experiments in full detail, aimed at providing a convenient platform for the study of learning algorithms.
  • FOG: a system for mining outerplanar graph patterns under BBP subgraph isomorphism.
  • GSSL: a randomized feature generation approach for Markov network structure learning.
  • MERCI: Identifying Discriminative Classification Based Motifs in Biological Sequences.
  • NSPDK: Neighborhood Subgraphs Pairwise Distance Kernel.
  • PIUS: Peptide Identification by Unbiased Search
  • ProbLog is a probabilistic Prolog, a probabilistic logic programming language.
  • PMCSFG: Pair-wise Maximum Common Subgraph Feature Generation.
  • PROFILE (Probabilistic First-Order Learning): a set of software tools for Statistical Relational Learning and Probabilistic ILP.
  • TODTLER: a deep transfer learning algorithm for Markov logic networks.
  • WFOMC: a system for performing lifted probabilistic inference by first-order knowledge compilation.
  • GC-FOVE: a system for performing lifted probabilistic inference by variable elimination.
  • kLogNLP: a kLog module for Graph Kernel-based Relational Learning of Natural Language.

Some older systems:

  • Claudien: a clausal discovery engine
  • Maccent: a maximum entropy modeling system
Last Updated on Monday, 17 November 2014 10:42