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MLCM: Multi-Label Confusion Matrix [PDF]
IEEE Access, 2022 Concise and unambiguous assessment of a machine learning algorithm is key to classifier design and performance improvement. In the multi-class classification task, where each instance can only be labeled as one class, the confusion matrix is a powerful ...
Mohammadreza Heydarian +2 more
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Comments on “MLCM: Multi-Label Confusion Matrix”
IEEE Access, 2023 In the paper “MLCM: Multi-Label Confusion Matrix” a method for computing the confusion matrix for the multi-label classification problem is proposed. Although the authors state that there is no similar work on computing confusion matrix for
Damir Krstinic +2 more
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The Matthews correlation coefficient (MCC) is more reliable than balanced accuracy, bookmaker informedness, and markedness in two-class confusion matrix evaluation. [PDF]
BioData Min, 2021 Evaluating binary classifications is a pivotal task in statistics and machine learning, because it can influence decisions in multiple areas, including for example prognosis or therapies of patients in critical conditions.
Chicco D, Tötsch N, Jurman G.
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Monte Carlo simulation with confusion matrix paradigm - A sample of internal consistency indices. [PDF]
Front Psychol, 2023 Monte Carlo simulation is a common method of providing empirical evidence to verify statistics used in psychological studies. A representative set of conditions should be included in simulation studies.
Cheng Y +3 more
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Confusion matrix and minimum cross-entropy metrics based motion recognition system in the classroom. [PDF]
Sci Rep, 2022 This research proposes a motion recognition system for early detection of students' physical aggressive behavior in the classroom. The motion recognition system recognizes physical attacks so that teachers can resolve disputes early to reduce other ...
Wu MT.
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Hierarchical confusion matrix for classification performance evaluation [PDF]
Journal of the Royal Statistical Society Series C: Applied Statistics, 2023 Abstract This study proposes the novel concept of hierarchical confusion matrix, opening the door for popular confusion-matrix-based (flat) evaluation measures from binary classification problems, while considering the peculiarities of hierarchical classification problems.
Kevin Riehl +2 more
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Predictive System Implementation to Improve the Accuracy of Urine Self-Diagnosis with Smartphones: Application of a Confusion Matrix-Based Learning Model through RGB Semiquantitative Analysis. [PDF]
Sensors (Basel), 2022 Urinalysis, an elementary chemical reaction-based method for analyzing color conversion factors, facilitates examination of pathological conditions in the human body.
Kim SC, Cho YS.
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A Confusion Matrix for Evaluating Feature Attribution Methods
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023 The increasing use of deep learning models in critical areas of computer vision and the consequent need for insights into model behaviour have led to the development of numerous feature attribution methods. However, these attributions must be both meaningful and plausible to end-users, which is not always the case.
Arias Duart, Anna +3 more
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Ibn Al-Haitham Journal for Pure and Applied Sciences, 2023 In this research, a group of gray texture images of the Brodatz database was studied by building the features database of the images using the gray level co-occurrence matrix (GLCM), where the distance between the pixels was one unit and for four angles (
Haider S. Kaduhm +1 more
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TechnologiesThe paper addresses the issue of classification machine learning algorithm performance based on a novel probabilistic confusion matrix concept. The paper develops a theoretical framework which associates the proposed confusion matrix and the resulting ...
Ioannis Markoulidakis +1 more
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