• YACS

  • Referenced in 11 articles [sw04193]
  • YACS: A new learning classifier system using anticipation. A new and original trend ... Learning Classifier System (LCS) framework is focussed on latent learning. These new LCSs call upon...
  • ACS2

  • Referenced in 8 articles [sw03393]
  • anticipatory learning classifier system ACS, is provided. The documentation explains how to get started with...
  • GAssist

  • Referenced in 7 articles [sw08533]
  • GAssist is a Pittsburgh-style learning classifier system (LCS). It uses a standard genetic algorithm ... system incorporates several mechanisms to tackle data mining problems: A windowing system Incremental Learning with...
  • ExSTraCS

  • Referenced in 2 articles [sw28621]
  • Description and Evaluation of a Scalable Learning Classifier System. Algorithmic scalability is a major concern ... extended Michigan-style supervised learning classifier system that combined a set of powerful heuristics ... heterogeneous problem domains. While Michigan-style learning classifier systems are powerful and flexible learners, they ... effective strategy to dramatically improve learning classifier system scalability. ExSTraCS 2.0 addresses scalability with...
  • xcslib

  • Referenced in 2 articles [sw31105]
  • develop applications with Stewart Wilson’s learning classifier systems. The project is maintained and developed...
  • iLoc-Euk

  • Referenced in 37 articles [sw22434]
  • iLoc-Euk: a multi-label classifier for predicting the subcellular localization of singleplex and multiplex ... special notice. By introducing the ”multi-labeled learning” and ”accumulation-layer scale”, a new predictor ... used to deal with the systems containing both singleplex and multiplex proteins. As a demonstration ... benchmark dataset of eukaryotic proteins classified into the following 22 location sites: (1) acrosome...
  • 4eMka2

  • Referenced in 53 articles [sw16168]
  • user is simplified to preparation of the classified examples set and analysis of induced rules ... often case in similar systems e.g. UTA and Electre. These systems do require much more ... system should be more user friendly and require less additional time spent to learn...
  • iLoc-Virus

  • Referenced in 31 articles [sw22417]
  • iLoc-Virus: a multi-label learning classifier for identifying the subcellular localization of virus proteins ... challenging problem, particularly when the system concerned contains both single- and multiple-location proteins. Also...
  • MALLET

  • Referenced in 23 articles [sw10602]
  • topic modeling, information extraction, and other machine learning applications to text. MALLET includes sophisticated tools ... Decision Trees), and code for evaluating classifier performance using several commonly used metrics. In addition ... These methods are implemented in an extensible system for finite state transducers...
  • iLoc-Plant

  • Referenced in 18 articles [sw22419]
  • iLoc-Plant: a multi-label classifier for predicting the subcellular localization of plant proteins with ... notice. By introducing the “multi-labeled learning” approach, a new predictor, called iLoc-Plant ... used to deal with the systems containing both single- and multiple-location plant proteins ... benchmark dataset of plant proteins classified into the following 12 location sites: (1) cell membrane...
  • iLoc-Animal

  • Referenced in 20 articles [sw22427]
  • iLoc-Animal: a multi-label learning classifier for predicting subcellular localization of animal proteins. Predicting ... depth studies. By introducing the ”multi-label learning” approach, a new predictor, called iLoc-Animal ... used to deal with the systems containing both single- and multi-label animal (metazoan except ... prediction quality of a multi-label system in a rigorous way, five indices were introduced...
  • RIONA

  • Referenced in 9 articles [sw30227]
  • classification system combining rule induction and instance-based learning. The article describes a method combining ... empirical approaches to learning from examples: rule induction and instance-based learning. In our algorithm ... optimal neighbourhood is automatically induced during the learning phase. The empirical study shows the interesting ... comparable to an algorithm considering the whole learning set. The combination...
  • NEFCLASS-X

  • Referenced in 4 articles [sw27865]
  • Tool to Build Readable Fuzzy Classifiers. Neuro-fuzzy classification systems offer a means of obtaining ... fuzzy classification rules by a learning algorithm. Although it is usually no problem to find ... suitable fuzzy classifier by learning from data, it can, however, be hard to obtain...
  • April

  • Referenced in 3 articles [sw25423]
  • Inductive Logic Programming (ILP) is a Machine Learning research field that has been quite successful ... relational domains. ILP systems use a set of pre-classified examples (positive and negative ... prior knowledge to learn a theory in which positive examples succeed and the negative examples ... this paper we present a novel ILP system called April, capable of exploring several parallel...
  • iRSpot-EL

  • Referenced in 29 articles [sw24776]
  • with an ensemble learning approach. MOTIVATION: Coexisting in a DNA system, meiosis and recombination ... based auto-cross covariance into an ensemble classifier of clustering approach. Five-fold cross tests...
  • iCaRL

  • Referenced in 6 articles [sw37989]
  • iCaRL: Incremental Classifier and Representation Learning. A major open problem on the road to artificial ... intelligence is the development of incrementally learning systems that learn about more and more concepts ... training strategy, iCaRL, that allows learning in such a class-incremental way: only the training ... classes can be added progressively. iCaRL learns strong classifiers and a data representation simultaneously. This...
  • See5

  • Referenced in 9 articles [sw12178]
  • Learning (although these don’t hurt, either!) RuleQuest provides C source code so that classifiers ... embedded in your organization’s own systems...
  • OpenDT

  • Referenced in 2 articles [sw12787]
  • trees. Machine learning has benefited tremendously from the use of Multiple Classifier Systems, both...
  • MagNet

  • Referenced in 5 articles [sw41285]
  • important. Attempts to secure deep learning systems either target specific attacks or have been shown ... neural network classifiers against adversarial examples. MagNet does not modify the protected classifier or know ... reformer network. Different from previous work, MagNet learns to differentiate between normal and adversarial examples...
  • SHIELD

  • Referenced in 7 articles [sw20121]
  • homomorphic implementation of encrypted data-classifiers. Homomorphic encryption (HE) systems enable computations on encrypted data ... this work, we describe an optimized Ring Learning With Errors (RLWE) based implementation...