Results 11 to 20 of about 3,073,916 (262)
Multiclass Classification Performance Curve
IEEE Access, 2022 Quality of predictive models is a critical factor. Many evaluation measures have been proposed for binary and multi–class datasets. However, less attention has been paid to graphical representation of the classification performance, where the ROC ...
Jesus S. Aguilar-Ruiz, Marcin Michalak
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PLoS ONE, 2014 Classification methods used in microarray studies for gene expression are diverse in the way they deal with the underlying complexity of the data, as well as in the technique used to build the classification model.
Putri W Novianti +2 more
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Performance reproducibility index for classification [PDF]
Bioinformatics, 2012 Abstract Motivation: A common practice in biomarker discovery is to decide whether a large laboratory experiment should be carried out based on the results of a preliminary study on a small set of specimens. Consideration of the efficacy of this approach motivates the introduction of a probabilistic measure, for whether a classifier ...
Mohammadmahdi R, Yousefi +1 more
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Metamodelling of Noise to Image Classification Performance
IEEE Access, 2023 Machine Learning (ML) has made its way into a wide variety of advanced applications, where high accuracies can be achieved when these ML models are evaluated in the same context as they were trained and validated on.
Jens De Hoog +4 more
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Early detection of student degree-level academic performance using educational data mining [PDF]
PeerJ Computer Science, 2023 Higher educational institutes generate massive amounts of student data. This data needs to be explored in depth to better understand various facets of student learning behavior.
Areej Fatemah Meghji +5 more
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Using Word Embeddings in Twitter Election Classification [PDF]
, 2016 Word embeddings and convolutional neural networks (CNN) have attracted extensive attention in various classification tasks for Twitter, e.g. sentiment classification.
Macdonald, Craig +2 more
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IET Computer Vision, 2020 Fisher kernels derived from stochastic probabilistic models such as restricted and deep Boltzmann machines have shown competitive visual classification results in comparison to widely popular deep discriminative models.
Sarah Ahmed, Tayyaba Azim
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Sensors, 2023 Hepatocellular Carcinoma (HCC) is the most frequent malignant liver tumor and the third cause of cancer-related deaths worldwide. For many years, the golden standard for HCC diagnosis has been the needle biopsy, which is invasive and carries risks ...
Delia-Alexandrina Mitrea +5 more
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Learning distance to subspace for the nearest subspace methods in high-dimensional data classification [PDF]
, 2018 The nearest subspace methods (NSM) are a category of classification methods widely applied to classify high-dimensional data. In this paper, we propose to improve the classification performance of NSM through learning tailored distance metrics from ...
Dong, M., Xue, J-H., Zhu, R.
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Improving BCI performance after classification
Proceedings of the 14th ACM international conference on Multimodal interaction, 2012 Brain-computer interfaces offer a valuable input modality, which unfortunately comes also with a high degree of uncertainty. There are simple methods to improve detection accuracy after the incoming brain activity has already been classified, which can be divided into (1) gathering additional evidence from other sources of information, and (2 ...
Plass - Oude Bos, D. +3 more
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