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A bayesian framework for case-based reasoning
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/0470013192.bsa231openalex-snapshot
Finite Mixture Distributions
inferredcites →https://doi.org/10.1002/9780470316849openalex-snapshot
Multivariate Density Estimation
inferredcites →https://doi.org/10.1007/3-540-58330-0_74openalex-snapshot
Analogical asides on case-based reasoning
inferredcites →https://doi.org/10.1007/3-540-58330-0_83openalex-snapshot
Massively parallel case-based reasoning with probabilistic similarity metrics
inferredcites →https://doi.org/10.1007/978-94-009-5897-5openalex-snapshot
Finite Mixture Distributions
inferredcites →https://doi.org/10.1007/bf00153759openalex-snapshot
Instance-Based Learning Algorithms
inferredcites →https://doi.org/10.1007/bf00153760openalex-snapshot
Information-Based Evaluation Criterion for Classifier's Performance
inferredcites →https://doi.org/10.1007/bf00155578openalex-snapshot
An introduction to case-based reasoning
inferredcites →https://doi.org/10.1007/bfb0017010openalex-snapshot
On estimating probabilities in tree pruning
inferredcites →https://doi.org/10.1016/0004-3702(85)90016-5openalex-snapshot
Heuristic classification
inferredcites →https://doi.org/10.1016/b978-0-934613-64-4.50011-6openalex-snapshot
AutoClass: A Bayesian Classification System
inferredcites →https://doi.org/10.1016/b978-1-55860-335-6.50043-xopenalex-snapshot
Prototype and Feature Selection by Sampling and Random Mutation Hill Climbing Algorithms
inferredcites →https://doi.org/10.1017/s0269888900007098openalex-snapshot
Case-based reasoning: A review
inferredcites →https://doi.org/10.1023/a:1022631118932openalex-snapshot
Very Simple Classification Rules Perform Well on Most Commonly Used Datasets
inferredcites →https://doi.org/10.1023/a:1022691111431openalex-snapshot
Integrating Feature Extraction and Memory Search
inferredcites →https://doi.org/10.1057/jors.1996.92openalex-snapshot
Probabilistic Reasoning and Bayesian Belief Networks
inferredcites →https://doi.org/10.1080/00401706.1993.10485361openalex-snapshot
Multivariate Density Estimation, Theory, Practice, and Visualbation
inferredcites →https://doi.org/10.1080/00401706.1995.10484383openalex-snapshot
Machine Learning, Neural and Statistical Classification
inferredcites →https://doi.org/10.1109/icnn.1993.298594openalex-snapshot
Bayesian case-based reasoning with neural networks
inferredcites →https://doi.org/10.1109/tit.1967.1053964openalex-snapshot
Nearest neighbor pattern classification
inferredcites →https://doi.org/10.1111/j.2517-6161.1977.tb01600.xopenalex-snapshot
Maximum Likelihood from Incomplete Data Via the EM Algorithm
inferredcites →https://doi.org/10.1162/neco.1994.6.2.181openalex-snapshot
Hierarchical Mixtures of Experts and the EM Algorithm
inferredcites →https://doi.org/10.1613/jair.279openalex-snapshot
Improved Use of Continuous Attributes in C4.5
inferredcites →https://doi.org/10.2307/2289504openalex-snapshot
Statistical Analysis of Finite Mixture Distributions.
inferredcites →https://doi.org/10.2307/2289883openalex-snapshot
Statistical Analysis With Missing Data
inferredcites →https://doi.org/10.2307/2531224openalex-snapshot
Statistical Analysis of Finite Mixture Distributions.
inferredcites →https://doi.org/10.48550/arxiv.1302.3567openalex-snapshot
Efficient Approximations for the Marginal Likelihood of Incomplete Data Given a Bayesian Network
inferredcites →https://doi.org/10.48550/arxiv.1302.4964openalex-snapshot
Estimating Continuous Distributions in Bayesian Classifiers
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/3-540-46119-1_36openalex-snapshot
An Application of Case-Based Reasoning to the Adaptive Management of Wireless Networks
inferred← citeshttps://doi.org/10.1007/3-540-62858-4_96openalex-snapshot
Case-based learning: Beyond classification of feature vectors
inferred← citeshttps://doi.org/10.1007/3-540-63233-6_530openalex-snapshot
A probabilistic model for case-based reasoning
inferred← citeshttps://doi.org/10.1007/3-540-64574-8_464openalex-snapshot
Comparing soft computing methods in prediction of manufacturing data
inferred← citeshttps://doi.org/10.1007/978-3-322-89950-7_8openalex-snapshot
Einsatz von Case-Based Reasoning zur Kundenunterstützung im Internet
inferred← citeshttps://doi.org/10.1007/978-3-540-28631-8_15openalex-snapshot
Software Design Retrieval Using Bayesian Networks and WordNet
inferred← citeshttps://doi.org/10.1007/978-3-540-89197-0_39openalex-snapshot
Fault Resolution in Case-Based Reasoning
inferred← citeshttps://doi.org/10.1007/978-3-642-14932-0_12openalex-snapshot
PCOPM: A Probabilistic CBR Framework for Obesity Prescription Management
inferred← citeshttps://doi.org/10.1007/bfb0026675openalex-snapshot
Bayes optimal instance-based learning
inferred← citeshttps://doi.org/10.1007/s13748-020-00227-xopenalex-snapshot
Fault diagnosis under uncertain situations within a Bayesian knowledge-intensive CBR system
inferred← citeshttps://doi.org/10.1016/s0888-613x(00)00062-1openalex-snapshot
Similarity-based inference as evidential reasoning
inferred← citeshttps://doi.org/10.1016/s0950-7051(98)00066-5openalex-snapshot
The omnipresence of case-based reasoning in science and application
inferred← citeshttps://doi.org/10.1109/ivs.2013.6629544openalex-snapshot
A learning concept for behavior prediction in traffic situations
inferred← citeshttps://doi.org/10.1109/kdex.1997.629864openalex-snapshot
Hypothesis testing approach on noisy cases in RICAD
inferred← citeshttps://doi.org/10.2200/s00490ed1v01y201303aim020openalex-snapshot
Case-Based Reasoning: A Concise Introduction
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