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Titlebook: 12th International Conference on Information Systems and Advanced Technologies “ICISAT 2022”; Intelligent Informat Mohamed Ridda Laouar,Val

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樓主: ACE313
51#
發(fā)表于 2025-3-30 11:20:36 | 只看該作者
52#
發(fā)表于 2025-3-30 13:58:46 | 只看該作者
53#
發(fā)表于 2025-3-30 16:54:32 | 只看該作者
Zusammenfassende Schlussbetrachtung,. The results demonstrated that combining MLP with the chosen (DRTs) methods increased the classification accuracy for almost all built models by at least 0.7%. In addition, they revealed a decrease in the classification accuracy using SVM as a classifier for almost all built models.
54#
發(fā)表于 2025-3-30 23:03:41 | 只看該作者
55#
發(fā)表于 2025-3-31 01:44:33 | 只看該作者
1.001 wirkungsvolle Fragen für den Vertriebwere conduct on ten microarray datasets, the results indicate that using univariate filter feature selection methods (MI, F-score, Fisher score) outperformed multivariate filter feature selection methods (MRMR, CMIM).
56#
發(fā)表于 2025-3-31 07:13:12 | 只看該作者
Wie sich der Vertrieb ver?ndertd the models using the majority voting method, taking into account the OBS of each one. The results of five challenging datasets show that the ensemble model technique improves the performance of single-use models and outperforms similar state-of-the-arts.
57#
發(fā)表于 2025-3-31 11:40:16 | 只看該作者
58#
發(fā)表于 2025-3-31 16:06:16 | 只看該作者
https://doi.org/10.1007/978-3-658-43606-3e proven to be more efficient for better data transmission throughout the network lifetime. In this paper, we review the state-of-the-art about clustering techniques by making comparisons between them according to different criteria. The aim is make an objective assessment by giving their potential advantages and limitations.
59#
發(fā)表于 2025-3-31 20:16:15 | 只看該作者
60#
發(fā)表于 2025-3-31 22:03:11 | 只看該作者
Wie sich der Vertrieb ver?ndertbility of the results. From analytical point of view, our current research focuses on the study of the correlations between time series. We recommend a complex framework with three main modules to extend the sphere of the input time series based on a systematic approach and examine the reliability of the discovered correlations.
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