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Rejection Threshold Optimization using 3D ROC Curves: Novel Findings on Biomedical Datasets
2021
International Journal of Intelligent Systems and Applications in Engineering
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Considering classification with reject option, we need to represent the tradeoff between TP, FP and rejection rates. ...
Reject option is introduced in classification tasks to prevent potential misclassifications. ...
Conclusion In this study, we have presented a novel approach to classification with reject option: rejection threshold optimization based on 3D ROC analysis. ...
doi:10.18201/ijisae.2021167933
fatcat:zgk5n3eoavfyvoxnmogxnkrsuy
A risk bound for ensemble classification with a reject option
2011
2011 IEEE Statistical Signal Processing Workshop (SSP)
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In this work, a bound on generalization error for ensemble classification with a reject option is derived that involves two intuitive properties of the ensemble: average strength and mean correlation. ...
In decision support scenarios, it is often of interest for automatic classification algorithms to abstain from making decisions on the most uncertain signals; this is known as classification with a reject ...
Such abstention is known as classification with a reject option [1, 2] . ...
doi:10.1109/ssp.2011.5967817
fatcat:parvujqwcjfulpk6baevefyxem
Practical Ensemble Classification Error Bounds for Different Operating Points
2013
IEEE Transactions on Knowledge and Data Engineering
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Significantly, the bounds are empirically shown to have much practical utility in determining optimal parameters for classification with a reject option, classification for ultralow probability of false ...
A generalization bound for ensemble classification at the standard operating point has been developed based on two interpretable properties of the ensemble: strength and correlation, using the Chebyshev ...
ACKNOWLEDGMENTS Part of this work was performed under the auspices of the US Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. ...
doi:10.1109/tkde.2012.219
fatcat:ykxlucephzbj5hrtqoc7pkxtoa
The interaction between classification and reject performance for distance-based reject-option classifiers
2006
Pattern Recognition Letters
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We show how the operating characteristics can be used for both model selection, and in aiding in the choice of the reject threshold. ...
Consider the class of problems in which a target class is well-defined, and an outlier class is ill-defined. ...
A special mention is given to the anonymous reviewers who helped clarify some aspects of this work. ...
doi:10.1016/j.patrec.2005.10.015
fatcat:qs6yv3qwhrbh7iojuv3fdscxcu
Linear Classifier with Reject Option for the Detection of Vocal Fold Paralysis and Vocal Fold Edema
2009
EURASIP Journal on Advances in Signal Processing
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The optimal operating point of the linear classifier is specified with and without reject option. First results using utterances of the "rainbow passage" are also reported for completeness. ...
The reject option is shown to yield statistically significant improvements in the accuracy of detecting the voice pathologies under study. ...
The superiority of the linear classifier with reject option is demonstrated in Figure 5 , where the convex hull of the ROC curves with reject option (solid line) and without reject option (dashed line ...
doi:10.1155/2009/203790
fatcat:nnxpcvr3fzcelon2l4nlheo3ou
GMM improves the reject option in hierarchical classification for fish recognition
2014
IEEE Winter Conference on Applications of Computer Vision
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A reject option in classification is useful to filter less confident decisions of known classes or to detect and remove untrained classes. ...
This paper presents a novel rejection system in a hierarchical classification method for fish species recognition. ...
Result analysis and discussions The system performance of fish recognition is evaluated by Average Recall (AR) and Average Precision (AP), which are averaged by all classes with reject option. ...
doi:10.1109/wacv.2014.6836076
dblp:conf/wacv/HuangBF14
fatcat:f3ogewugtzakvi5qco2qxhtgyq
A Survey on Sentiment Classification for Product Aspect Ranking
2015
International Journal of Computer Applications
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A large number of reviews for the product are available on the internet .To classify these reviews is very difficult task. ...
In this paper, we study the survey of different techniques for sentiment classification. ...
Results were obtained without reject option and with reject option. SVM gains higher accuracy without reject option and NBSVM gains higher accuracy with reject option. ...
doi:10.5120/ijca2015907595
fatcat:cvx47lgopbcphnrhmo6kffrgla
Optimal Rejection Function Meets Character Recognition Tasks
[article]
2022
arXiv
pre-print
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This rejection function is trained together with a classification function under the framework of Learning-with-Rejection (LwR). ...
The highlights of LwR are: (1) the rejection strategy is not heuristic but has a strong background from a machine learning theory, and (2) the rejection function can be trained on an arbitrary feature ...
writer with a rejection option. ...
arXiv:2203.09151v1
fatcat:mrbg2w5ar5hjtpm24zzpcvd7wm
Accuracy-Rejection Curves (ARCs) for Comparing Classification Methods with a Reject Option
2010
Journal of machine learning research
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These comparisons are based on classification schemes in which all samples are classified, regardless of the degree of confidence associated with the classification of a particular sample on the basis ...
We describe an approach in which the performance of different classifiers is compared, with the possibility of rejection, based on several reject areas. ...
Acknowledgments We would like to thank the Government of France, High Education Commission (HEC) Government of Pakistan, Societe Francaise d'Exportation des Ressources Educatives (SFERE), France, University ...
dblp:journals/jmlr/NadeemZH10
fatcat:mjewn2azkjbhndffn2qesf7rta
Rejection Strategies for Learning Vector Quantization – A Comparison of Probabilistic and Deterministic Approaches
[chapter]
2014
Advances in Intelligent Systems and Computing
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We present prototype-based classification schemes, e. g. learning vector quantization, with cost-function-based and geometrically motivated reject options. ...
We demonstrate that reject options improve the accuracy of the models in most cases, and that the performance of the proposed schemes is comparable to the optimal reject option of the Bayes classifier ...
Given a certainty measure r : R n → R for the classification of a point x and a threshold θ ∈ R, a simple reject option is to reject x iff r(x) < θ. ...
doi:10.1007/978-3-319-07695-9_10
fatcat:kuklema6engwrmxd7m4yjdogjm
Speech Emotion Recognition with a Reject Option
2019
Interspeech 2019
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We use two different criteria to develop a SER system with a reject option, where it can accept or reject a sample as needed. ...
This paper proposes a classification technique with a reject option using deep neural networks (DNNs) that increases its performance by selectively trading its coverage in the testing set. ...
Results and Analysis This section evaluates the use of a reject option in SER problems. ...
doi:10.21437/interspeech.2019-1842
dblp:conf/interspeech/SridharB19
fatcat:yixgukba5vgojlbmq6dsmzlbly
Pattern rejection strategies for the design of self-paced EEG-based Brain-Computer Interfaces
2008
Pattern Recognition (ICPR), Proceedings of the International Conference on
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Concerning the reject option, RC outperformed a specialized reject classifier which outperformed TRF. ...
Overall, the best results were obtained using the RC reject option and non-linear classifiers such as a Gaussian support vector machine, a fuzzy inference system or a radial basis function network. ...
The SC and RC reject options should take advantage of discriminant classifiers because they consider the rejection problem as a simple classification task. ...
doi:10.1109/icpr.2008.4761454
dblp:conf/icpr/LotteML08
fatcat:zh3a4cdepvcidprb75owr2gm7u
On the Feature Selection Methods and Reject Option Classifiers for Robust Cancer Prediction
2019
IEEE Access
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Reject Option (RO) classifiers have been used to improve the predictive accuracy of classifiers for cancer like complex problems. ...
Therefore, both FS methods and ML algorithms with RO need to be considered for robust classification. ...
Overall results depict that better classification for the colon dataset can be achieved with reject option. ...
doi:10.1109/access.2019.2944295
fatcat:j5hmitdb4rg7riz3657ooprira
PyMDA: microcrystal data assembly using Python
2020
Journal of Applied Crystallography
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The recent developments at microdiffraction X-ray beamlines are making microcrystals of macromolecules appealing subjects for routine structural analysis. ...
Microcrystal diffraction data collected at synchrotron microdiffraction beamlines may be radiation damaged with incomplete data per microcrystal and with unit-cell variations. ...
Crystal rejection Each of the N classes with data completeness higher than 90% may be used for crystal rejection with an option --rjxtal. ...
doi:10.1107/s160057671901673x
pmid:32047415
pmcid:PMC6998775
fatcat:kfjyla27rzfsvizlhtdvx4oh2u
Toward Improving the Reliability of Discrete Movement Recognition of sEMG Signals
2022
Applied Sciences
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The proposed algorithm can reject the trained movements with low reliability and is efficient in rejecting the untrained movements, thus enhancing the reliability of the myoelectric control system. ...
Currently, the classification accuracy of surface electromyography (sEMG) signals is high in literature, but the conventional recognition system may classify untrained movements or the trained movements ...
A literature review on classification with reject options is introduced in Section 2. ...
doi:10.3390/app12073374
fatcat:2enzjz7tdvcrlhbps76gouuo6i
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