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Experimental results on benchmark datasets demonstrate that the proposed system is robust and efficient.
Extensive experiments on five datasets demonstrate that the GESR-LR method outperform the state-of-the-art methods.
Experiments conducted on real datasets demonstrate that the attack is both accurate and resilient to sanitization mechanisms.
The experimental results on five benchmark datasets demonstrate that the proposed approach outperforms several state-of-the-art works.
Experiments performing the clustering and classification on time series datasets demonstrate that the performance of the proposed method outperforms PVQA.
Also, the test results of the forest datasets demonstrate that the mean errors of the proposed algorithm are compatible with those from other algorithms.
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The recognition accuracy achieved on these datasets demonstrates that the proposed approach has an abundant discriminating power of recognizing the variety of actions.
Experiments based on benchmark datasets demonstrated that the proposed approach provides a statistically significant improvement in terms of the classification performance compared with state-of-the-art decomposition strategies.
Benchmarking of the hierarchical method on in silico datasets demonstrates that the method generally outperforms the standard CSI algorithm, by allowing propagation of information via the hypernetwork.
Nevertheless, the fact that sex-adjusted results showed significant association of WC with TFI in both datasets demonstrates that the stratification due to sex may be minimal.
Tests on the experimental datasets demonstrated that the informativeness metric was more accurate in uncovering the number of clusters that would summarize the data into its most distinct set of cluster patterns relevant to the cell types being studied.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com