• LERS

  • Referenced in 122 articles [sw08637]
  • paper presents the system LERS for rule induction. The system handles inconsistencies in the input ... user has the choice to use the machine learning approach or the knowledge acquisition approach...
  • Dyna

  • Referenced in 12 articles [sw23357]
  • being used for parsing, machine translation, morphological analysis, grammar induction, and finite-state modeling...
  • NEURObjects

  • Referenced in 3 articles [sw00617]
  • neural networks and fast prototyping of inductive machine learning applications. We present NEURObjects design issues...
  • ENDER

  • Referenced in 15 articles [sw12831]
  • decision rules. Induction of decision rules plays an important role in machine learning. The main...
  • MPTP 0.2

  • Referenced in 50 articles [sw02589]
  • which the premises are selected by a machine-learning system trained on previous proofs ... This situation suggests that even a simple inductive or deductive system trained on formal mathematics...
  • IGLUE

  • Referenced in 4 articles [sw31671]
  • IGLUE: a lattice-based constructive induction system. A machine learning (ML) system which combines lattice...
  • TerpreT

  • Referenced in 2 articles [sw29483]
  • Probabilistic Programming Language for Program Induction. We study machine learning formulations of inductive program synthesis ... outputs. Our aims are to develop new machine learning approaches based on neural networks...
  • April

  • Referenced in 3 articles [sw25423]
  • Inductive Logic Programming System. Inductive Logic Programming (ILP) is a Machine Learning research field that...
  • LFOIL

  • Referenced in 7 articles [sw02759]
  • LFOIL: linguistic rule induction in the label semantics framework. Label semantics is a random ... modelling with words. In previous work, several machine learning algorithms based on this framework have ... paper, we introduce a new linguistic rule induction algorithm based on Quinlan’s FOIL algorithm...
  • Metaopt

  • Referenced in 8 articles [sw34722]
  • Learning efficient logic programs. When machine learning programs from data, we ideally want to learn ... efficient rather than inefficient programs. However, existing inductive logic programming (ILP) techniques cannot distinguish between ... knowledge, Metaopt is the first machine learning approach that, given sufficient numbers of training examples...
  • IIPS

  • Referenced in 6 articles [sw01329]
  • propose the IIPS framework for specifying inductive inference problems. Unlike the specification outline given ... examples. The framework is suited to specifying machine-discovery problems...
  • kFOIL

  • Referenced in 12 articles [sw23358]
  • kFOIL algorithm integrates the well-known inductive logic programming system FOIL with kernel methods ... performance obtained by a support vector machine based on the resulting kernel. In this...
  • Psi-calculi

  • Referenced in 11 articles [sw28573]
  • formalisation is to keep the machine checked proofs as close to their pen-and-paper ... sequences as atomic elements, and creating custom induction and inversion rules that to remove...
  • IDP3

  • Referenced in 9 articles [sw22941]
  • modeling language: modeling and solving some machine learning and data mining problems with IDP3. This ... supports first-order logic enriched with types, inductive definitions, aggregates and partial functions. It offers ... selected from problems that arose within machine learning and data mining research. These research areas...
  • ILPME

  • Referenced in 2 articles [sw27486]
  • ILPME is a nonmonotonic ILP (Inductive Logic Programming) system that learns from multiple distinct examples ... produced several datasets which have given the machine learning algorithms the opportunity to learn various ... these machine learning algorithms that aimed at learning logic programs, namely the Inductive Logic Programming ... learn from two popular datasets from machine learning community, namely bAbl (a question answering dataset...
  • CORElearn

  • Referenced in 5 articles [sw10624]
  • feature evaluation and ordinal evaluation. CORElearn is machine learning suite ported to R from standalone ... classification and regression trees with optional constructive induction and models in the leafs, random forests...
  • Louise

  • Referenced in 1 article [sw41513]
  • Learning. Louise (Patsantzis & Muggleton 2021) is a machine learning system that learns Prolog programs. Louise ... Inductive Logic Programming (ILP) (Muggleton, 1991). ILP is the branch of machine learning that studies...
  • conformalClassification

  • Referenced in 1 article [sw23838]
  • package implements Transductive Conformal Prediction (TCP) and Inductive Conformal Prediction (ICP) for classification problems. Conformal ... framework that complements the predictions of machine learning algorithms with reliable measures of confidence...
  • PrASP

  • Referenced in 2 articles [sw18512]
  • PrASP is both an uncertainty reasoning and machine learning software and a probabilistic logic programming ... research software platform for non-monotonic (inductive) probabilistic logic programming, our framework mainly targets applications...
  • iASA

  • Referenced in 3 articles [sw01494]
  • proposes. Moreover, our annotation algorithm exploits machine learning methods to correctly select instances ... greatly help users understand the rule induction and annotation process, so that they can focus...