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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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Confusion Matrix Stability Bounds for Multiclass Classification
, 2012 In this paper, we provide new theoretical results on the generalization properties of learning algorithms for multiclass classification problems. The originality of our work is that we propose to use the confusion matrix of a classifier as a measure of ...
Machart, Pierre, Ralaivola, Liva
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Journal of Innovation Information Technology and Application, 2023 Numerous factors can affect the development of infectious diseases that emerge. While many are the result of natural procedures, such as the gradual emergence of viruses over time, certain ones are the result of human activity.
Saviour Inyang, Imeh Umoren
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Visualizing Classification Results: Confusion Star and Confusion Gear
IEEE Access, 2022 Recent developments in machine learning applications are deeply concerned with the poor interpretability of most of these techniques. To gain some insights in the process of designing data-based models it is common to graphically represent the algorithm&#
Amalia Luque +3 more
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Jurnal Penelitian Fisika dan Aplikasinya, 2023 In detecting epileptic activity, medical experts examine the visual result of Electroencephalography signals. The visual analysis will take a lot of time and effort, due to a large amount of data.
Izaz Nadyah +2 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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Bootstrap Assessment of Crop Area Estimates Using Satellite Pixels Counting
Stats, 2022 Crop area estimates based on counting pixels over classified satellite images are a promising application of remote sensing to agriculture. However, such area estimates are biased, and their variance is a function of the error rates of the classification
Cristiano Ferraz +3 more
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Egyptian Journal of Remote Sensing and Space Sciences, 2022 Rice is one of the most important food staples in many countries, particularly Iran. Because irrigated rice production differs from other agricultural fields, this study developed a paddy field mapping model based on phenological aspects, various ...
Amir Hedayati +2 more
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Geoscience Data Journal, 2022 The confusion matrix has long been adopted as the ‘de facto’ and ‘de jure’ standard method of reporting on the thematic accuracy assessment of any land surface geospatial dataset.
Francisco J. Ariza‐López +3 more
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