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Using prior probabilities and density estimation for relational classification

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/3-540-63494-0_50openalex-snapshot

Feature construction with inductive logic programming: A study of quantitative predictions of biological activity by structural attributes

inferredcites →https://doi.org/10.1007/3-540-63494-0_65openalex-snapshot

Learning from positive data

inferredcites →https://doi.org/10.1007/3540635149_38openalex-snapshot

Part-of-speech tagging using Progol

inferredcites →https://doi.org/10.1007/3540635149_39openalex-snapshot

Maximum Entropy modeling with Clausal Constraints

inferredcites →https://doi.org/10.1007/3540635149_52openalex-snapshot

Probabilistic first-order classification

inferredcites →https://doi.org/10.1007/978-1-4899-4537-2_15openalex-snapshot

Learning classification trees

inferredcites →https://doi.org/10.1007/bf01889584openalex-snapshot

Learning classification trees

inferredcites →https://doi.org/10.1007/bfb0026693openalex-snapshot

Predicate invention and learning from positive examples only

inferredcites →https://doi.org/10.1016/0004-3702(90)90019-vopenalex-snapshot

An analysis of first-order logics of probability

inferredcites →https://doi.org/10.1016/0169-2070(93)90088-5openalex-snapshot

Journal of the Royal Statistical Society (B)

inferredcites →https://doi.org/10.1016/0890-5401(92)90061-jopenalex-snapshot

Probabilistic logic programming

inferredcites →https://doi.org/10.1023/a:1009815821645openalex-snapshot

Feature construction with Inductive Logic Programming: A Study of Quantitative Predictions of Biological Activity Aided by Structural Attributes

inferredcites →https://doi.org/10.1080/00401706.1995.10484383openalex-snapshot

Machine Learning, Neural and Statistical Classification

inferredcites →https://doi.org/10.1111/j.2517-6161.1993.tb01466.xopenalex-snapshot

Bayesian Computation Via the Gibbs Sampler and Related Markov Chain Monte Carlo Methods

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/11536314_5openalex-snapshot

A Framework for Set-Oriented Computation in Inductive Logic Programming and Its Application in Generalizing Inverse Entailment

inferred← citeshttps://doi.org/10.1007/3-540-44960-4_9openalex-snapshot

Solving Selection Problems Using Preference Relation Based on Bayesian Learning

inferred← citeshttps://doi.org/10.1007/3-540-48751-4_13openalex-snapshot

Application of Different Learning Methods to Hungarian Part-of-Speech Tagging

inferred← citeshttps://doi.org/10.1007/978-3-540-30109-7_20openalex-snapshot

Improving Rule Evaluation Using Multitask Learning

inferred← citeshttps://doi.org/10.1007/bfb0027303openalex-snapshot

Inductive Logic Programming

inferred← citeshttps://doi.org/10.1023/a:1008741010967openalex-snapshot

A Default Logic Based Framework for Context-Dependent Reasoning with Lexical Knowledge

inferred← citeshttps://doi.org/10.1609/aaai.v28i1.9072openalex-snapshot

Relational One-Class Classification: A Non-Parametric Approach

inferred← citeshttps://doi.org/10.17169/refubium-12370openalex-snapshot

Planning and exploration in stochastic relational worlds

inferred← citeshttps://doi.org/10.26190/unsworks/17020openalex-snapshot

DEFT guessing: using inductive transfer to improve rule evaluation from limited data

inferred← citeshttps://doi.org/10.3233/kes-2007-11103openalex-snapshot

Solving selection problems combining relational learning and Bayesian learning

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