Fantasy
发表于 2025-3-30 11:31:49
Analyzing Classification Methods in Multi-label Tasksnnotation of images. This paper presents a comparative analysis of some existing multi-label classification methods applied to different domains. The main aim of this analysis is to evaluate the performance of such methods in different tasks and using different evaluation metrics.
佛刊
发表于 2025-3-30 14:27:28
Fiber Parameter Studies with the OTDRs has been done, but with cost functions that scale quadratically. Training a bottleneck classifier scales linearly, but still gives results comparable to or sometimes better than two earlier supervised methods.
Ige326
发表于 2025-3-30 18:00:19
J. J. Mecholsky,S. W. Freiman,S. M. Moreyexpression microarray datasets of different kinds of cancer. A comparative study with other classifiers such as Support Vector Machine (SVM), C4.5, naïve Bayes and k-Nearest Neighbor is performed. Our approach shows excellent results outperforming all other classifiers.
漫不经心
发表于 2025-3-31 00:02:37
https://doi.org/10.1007/978-3-662-52764-1The quality of the predictor is tested on a large test set of eye movement data and compared with the performance of two state-of-the-art saliency models on this data set. The proposed model demonstrates significant improvement – mean ROC score of 0.665 – over the selected baseline models with ROC scores of 0.625 and 0.635.
吗啡
发表于 2025-3-31 01:14:53
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Ischemia
发表于 2025-3-31 05:10:42
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CHASE
发表于 2025-3-31 11:39:37
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Infant
发表于 2025-3-31 14:21:09
Deep Bottleneck Classifiers in Supervised Dimension Reductions has been done, but with cost functions that scale quadratically. Training a bottleneck classifier scales linearly, but still gives results comparable to or sometimes better than two earlier supervised methods.
aspect
发表于 2025-3-31 19:15:53
Local Modeling Classifier for Microarray Gene-Expression Dataexpression microarray datasets of different kinds of cancer. A comparative study with other classifiers such as Support Vector Machine (SVM), C4.5, naïve Bayes and k-Nearest Neighbor is performed. Our approach shows excellent results outperforming all other classifiers.
有法律效应
发表于 2025-4-1 00:19:43
A Learned Saliency Predictor for Dynamic Natural ScenesThe quality of the predictor is tested on a large test set of eye movement data and compared with the performance of two state-of-the-art saliency models on this data set. The proposed model demonstrates significant improvement – mean ROC score of 0.665 – over the selected baseline models with ROC scores of 0.625 and 0.635.