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A Bagging Algorithm for Imprecise Classification in Cost-Sensitive Scenarios

https://doi.org/10.2139/ssrn.4810018
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inferredcites →https://doi.org/10.1007/3-540-45014-9_1openalex-extracted
Ensemble Methods in Machine Learning
inferredcites →https://doi.org/10.1007/978-3-030-50143-3_5openalex-extracted
Imprecise Classification with Non-parametric Predictive Inference
inferredcites →https://doi.org/10.1016/b978-1-55860-508-4.50025-9openalex-extracted
The Morgan Kaufmann Series in Data Management Systems
inferredcites →https://doi.org/10.1016/b978-1-55860-711-8.50025-3openalex-extracted
The Morgan Kaufmann Series in Data Management Systems
inferredcites →https://doi.org/10.1016/j.asoc.2013.08.014openalex-extracted
Cost-sensitive decision tree ensembles for effective imbalanced classification
inferredcites →https://doi.org/10.1016/j.asoc.2015.04.045openalex-extracted
Software defect prediction using cost-sensitive neural network
inferredcites →https://doi.org/10.1016/j.asoc.2022.108916openalex-extracted
A cost-sensitive Imprecise Credal Decision Tree based on Nonparametric Predictive Inference
inferredcites →https://doi.org/10.1016/j.csda.2013.02.009openalex-extracted
Classification with decision trees from a nonparametric predictive inference perspective
inferredcites →https://doi.org/10.1016/j.eswa.2015.04.042openalex-extracted
Example-dependent cost-sensitive decision trees
inferredcites →https://doi.org/10.1016/j.eswa.2016.12.020openalex-extracted
A comparative study on base classifiers in ensemble methods for credit scoring
inferredcites →https://doi.org/10.1016/j.eswa.2019.112944openalex-extracted
Bagging of credal decision trees for imprecise classification
inferredcites →https://doi.org/10.1016/j.eswa.2020.113275openalex-extracted
A cost-sensitive convolution neural network learning for control chart pattern recognition
inferredcites →https://doi.org/10.1016/j.eswa.2022.119232openalex-extracted
Optimal cost-sensitive credit scoring using a new hybrid performance metric
inferredcites →https://doi.org/10.1016/j.eswa.2023.120303openalex-extracted
Comparing cost sensitive classifiers by the false-positive to false- negative ratio in diagnostic studies
inferredcites →https://doi.org/10.1016/j.ijar.2017.03.008openalex-extracted
Cost-sensitive sequential three-way decision modeling using a deep neural network
inferredcites →https://doi.org/10.1016/j.inffus.2012.03.003openalex-extracted
Ensembles of decision trees based on imprecise probabilities and uncertainty measures
inferredcites →https://doi.org/10.1016/j.inffus.2020.10.017openalex-extracted
Adaptive ensemble of classifiers with regularization for imbalanced data classification
inferredcites →https://doi.org/10.1016/j.inffus.2022.08.021openalex-extracted
RuleCOSI+: Rule extraction for interpreting classification tree ensembles
inferredcites →https://doi.org/10.1016/j.inffus.2022.09.015openalex-extracted
Aggregation models in ensemble learning: A large-scale comparison
inferredcites →https://doi.org/10.1016/j.inffus.2022.12.014openalex-extracted
TSK fuzzy system fusion at sensitivity-ensemble-level for imbalanced data classification
inferredcites →https://doi.org/10.1016/j.ins.2019.11.041openalex-extracted
CREDO: Efficient and privacy-preserving multi-level medical pre-diagnosis based on ML-kNN
inferredcites →https://doi.org/10.1016/j.ins.2022.07.130openalex-extracted
A random approximate reduct-based ensemble learning approach and its application in software defect prediction
inferredcites →https://doi.org/10.1016/j.ins.2023.119261openalex-extracted
Efficient and privacy-preserving online diagnosis scheme based on federated learning in e-healthcare system
inferredcites →https://doi.org/10.1016/j.ins.2023.119447openalex-extracted
CATE: Contrastive augmentation and tree-enhanced embedding for credit scoring
inferredcites →https://doi.org/10.1016/j.ins.2023.119956openalex-extracted
Cost-sensitive thresholding over a two-dimensional decision region for fraud detection
inferredcites →https://doi.org/10.1016/j.ins.2024.120463openalex-extracted
StreamliNet: Cost-aware layer-wise neural network linearization for fast and accurate private inference
inferredcites →https://doi.org/10.1016/j.knosys.2015.08.012openalex-extracted
A cost sensitive decision tree algorithm with two adaptive mechanisms
inferredcites →https://doi.org/10.1016/s0378-3758(01)00201-4openalex-extracted
The naive credal classifier
inferredcites →https://doi.org/10.1023/a:1010933404324openalex-extracted
Random Forests
inferredcites →https://doi.org/10.1080/03081079.2011.607449openalex-extracted
Equivalence relations among dominance concepts on probability intervals and general credal sets
inferredcites →https://doi.org/10.1108/03684920610675283openalex-extracted
Uncertainty and Information: Foundations of Generalized Information Theory
inferredcites →https://doi.org/10.1109/tkde.2002.1000348openalex-extracted
An instance-weighting method to induce cost-sensitive trees
inferredcites →https://doi.org/10.1109/tr.2014.2316951openalex-extracted
Two-Stage Cost-Sensitive Learning for Software Defect Prediction
inferredcites →https://doi.org/10.1111/j.2517-6161.1996.tb02065.xopenalex-extracted
Inferences from Multinomial Data: Learning About a Bag of Marbles
inferredcites →https://doi.org/10.1142/s0218488512500353openalex-extracted
IMPRECISE CLASSIFICATION WITH CREDAL DECISION TREES
inferredcites →https://doi.org/10.1214/aoms/1177731944openalex-extracted
A Comparison of Alternative Tests of Significance for the Problem of $m$ Rankings
inferredcites →https://doi.org/10.2307/4615733openalex-extracted
A Simple Sequentially Rejective Multiple Test Procedure
inferredcites →https://doi.org/10.5555/1390681.1390701openalex-extracted
Learning Reliable Classifiers From Small or Incomplete Data Sets: The Naive Credal Classifier 2
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