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Test-cost sensitive classification on data with missing values
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Pattern Classification
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inferredcites →https://doi.org/10.1016/s0004-3702(02)00209-6openalex-snapshot
Learning cost-sensitive active classifiers☆☆This extends the short conference paper [19].
inferredcites →https://doi.org/10.1023/a:1007413511361openalex-snapshot
On the Optimality of the Simple Bayesian Classifier under Zero-One Loss
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The Use of Background Knowledge in Decision Tree Induction
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Test-Cost Sensitive Naive Bayes Classification
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Cost-Sensitive Classification: Empirical Evaluation of a Hybrid Genetic Decision Tree Induction Algorithm
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Types of Cost in Inductive Concept Learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1007/978-3-030-82193-7_15openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-319-54966-8_5openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-540-74958-5_52openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-540-76414-4_27openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-540-76719-0_44openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-642-16493-4_46openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-642-21222-2_30openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-642-23154-4_27openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-3-642-28487-8_40openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/978-981-15-5971-6_83openalex-snapshot
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inferred← citeshttps://doi.org/10.1007/s10489-019-01464-xopenalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.asoc.2010.12.012openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.asoc.2016.12.047openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.cor.2008.01.005openalex-snapshot
Towards optimal use of incomplete classification data
inferred← citeshttps://doi.org/10.1016/j.engappai.2022.105741openalex-snapshot
An adaptive machine learning algorithm for the resource-constrained classification problem
inferred← citeshttps://doi.org/10.1016/j.ins.2008.11.032openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.ins.2009.03.007openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.ins.2013.06.057openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.neucom.2017.04.010openalex-snapshot
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inferred← citeshttps://doi.org/10.1016/j.patrec.2010.05.028openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/icemis.2016.7745363openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/inista49547.2020.9194615openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/jcai.2009.118openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/mis.2007.67openalex-snapshot
Domain-Driven, Actionable Knowledge Discovery
inferred← citeshttps://doi.org/10.1109/tkde.2007.1042openalex-snapshot
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inferred← citeshttps://doi.org/10.1109/tsmcb.2009.2012504openalex-snapshot
Rough Neuro-Fuzzy Structures for Classification With Missing Data
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inferred← citeshttps://doi.org/10.1145/2905055.2905273openalex-snapshot
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inferred← citeshttps://doi.org/10.12733/jics20105758openalex-snapshot
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inferred← citeshttps://doi.org/10.1371/journal.pone.0307146openalex-snapshot
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inferred← citeshttps://doi.org/10.14569/ijacsa.2021.0120309openalex-snapshot
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inferred← citeshttps://doi.org/10.22323/1.259.0056openalex-snapshot
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