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Inference-Based Naïve Bayes: Turning Naïve Bayes Cost-Sensitive

https://doi.org/10.1109/tkde.2012.196

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What this work says

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

inferredcites →https://doi.org/10.1006/jcss.1997.1504openalex-snapshot

A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting

inferredcites →https://doi.org/10.1007/3-540-36755-1_23openalex-snapshot

Class Probability Estimation and Cost-Sensitive Classification Decisions

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An Empirical Study of MetaCost Using Boosting Algorithms

inferredcites →https://doi.org/10.1007/978-0-387-21606-5openalex-snapshot

The Elements of Statistical Learning

inferredcites →https://doi.org/10.1007/bf00058655openalex-snapshot

Bagging predictors

inferredcites →https://doi.org/10.1007/bfb0026690openalex-snapshot

Naive bayesian classifier committees

inferredcites →https://doi.org/10.1007/s10115-007-0079-1openalex-snapshot

Instance weighting versus threshold adjusting for cost-sensitive classification

inferredcites →https://doi.org/10.1007/s10994-005-4258-6openalex-snapshot

Not So Naive Bayes: Aggregating One-Dependence Estimators

inferredcites →https://doi.org/10.1016/b978-1-55860-335-6.50034-9openalex-snapshot

Reducing Misclassification Costs

inferredcites →https://doi.org/10.1016/j.csda.2005.06.007openalex-snapshot

On optimum choice of k in nearest neighbor classification

inferredcites →https://doi.org/10.1016/j.knosys.2006.11.008openalex-snapshot

A decision tree-based attribute weighting filter for naive Bayes

inferredcites →https://doi.org/10.1016/s0933-3657(02)00058-1openalex-snapshot

Principles of Data Mining

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On the Optimality of the Simple Bayesian Classifier under Zero-One Loss

inferredcites →https://doi.org/10.1023/a:1007465528199openalex-snapshot

Bayesian Network Classifiers

inferredcites →https://doi.org/10.1023/a:1009778005914openalex-snapshot

On Bias, Variance, 0/1—Loss, and the Curse-of-Dimensionality

inferredcites →https://doi.org/10.1023/a:1018054314350openalex-snapshot

Bagging Predictors

inferredcites →https://doi.org/10.1073/pnas.87.23.9193openalex-snapshot

Multisurface method of pattern separation for medical diagnosis applied to breast cytology.

inferredcites →https://doi.org/10.1080/00401706.1999.10485951openalex-snapshot

Statistical Learning Theory

inferredcites →https://doi.org/10.1109/35.41401openalex-snapshot

Pattern classification using neural networks

inferredcites →https://doi.org/10.1109/icdm.2004.10030openalex-snapshot

Learning weighted naive Bayes with accurate ranking

inferredcites →https://doi.org/10.1109/tit.1967.1053964openalex-snapshot

Nearest neighbor pattern classification

inferredcites →https://doi.org/10.1109/tkde.2002.1000348openalex-snapshot

An instance-weighting method to induce cost-sensitive trees

inferredcites →https://doi.org/10.1109/tkde.2006.17openalex-snapshot

Training cost-sensitive neural networks with methods addressing the class imbalance problem

inferredcites →https://doi.org/10.1109/tkde.2008.234openalex-snapshot

A Novel Bayes Model: Hidden Naive Bayes

inferredcites →https://doi.org/10.1111/j.1467-985x.1997.00078.xopenalex-snapshot

Statistical Classification Methods in Consumer Credit Scoring: A Review

inferredcites →https://doi.org/10.1145/1835804.1835857openalex-snapshot

Learning with cost intervals

inferredcites →https://doi.org/10.1145/312129.312220openalex-snapshot

MetaCost

inferredcites →https://doi.org/10.1145/502512.502540openalex-snapshot

Learning and making decisions when costs and probabilities are both unknown

inferredcites →https://doi.org/10.1214/07-aos537openalex-snapshot

Choice of neighbor order in nearest-neighbor classification

inferredcites →https://doi.org/10.1214/aos/1028144844openalex-snapshot

Classification by pairwise coupling

inferredcites →https://doi.org/10.1287/mnsc.1040.0296openalex-snapshot

Customer Targeting: A Neural Network Approach Guided by Genetic Algorithms

inferredcites →https://doi.org/10.1509/jmkr.43.2.276openalex-snapshot

Bagging and Boosting Classification Trees to Predict Churn

inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot

SMOTE: Synthetic Minority Over-sampling Technique

inferredcites →https://doi.org/10.2307/2344977openalex-snapshot

Pattern Classification and Scene Analysis.

inferredcites →https://doi.org/10.2307/2530946openalex-snapshot

Classification and Regression Trees.

inferredcites →https://doi.org/10.26180/14973813openalex-snapshot

Semi-naive Bayesian classification

inferredcites →https://doi.org/10.3233/ida-2000-4603openalex-snapshot

Iterative Bayes

inferredcites →https://doi.org/10.3233/ida-2007-11505openalex-snapshot

An evaluation of Naive Bayes variants in content-based learning for spam filtering

inferredcites →https://doi.org/10.48550/arxiv.1212.2487openalex-snapshot

Locally Weighted Naive Bayes

inferredcites →https://doi.org/10.5555/1248547.1248548openalex-snapshot

Statistical Comparisons of Classifiers over Multiple Data Sets

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