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This special issue is poised to contribute to a conversation that is just beginning, with rich reflections from a variety of orientations, methods, traditions, contexts, and regions.
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The average orientations method provides the closest results to human perception, while the other algorithms proved themselves to be very competitive.
The layer-by-layer coating of oriented films demonstrated by this method is found to be a unique feature which overcomes cumbersome procedures in the conventional orientation methods.
Few orientation methods are highly accurate; this is particularly true for methods applied to three-dimensional models obtained by surface scanning, a technique whose special features make it a powerful tool in forensic contexts.
We also introduced a novel ensemble technique for causal orientation that combines decisions of individual causal orientation methods.
Finally, prior to application of the causal orientation methods, we standardized the data to mean zero and standard deviation one.
This work represents a first step towards establishing context for practical use of causal orientation methods in the genomics domain.
This approach follows the practices of previously published applications of causal orientation methods by their inventors [ 16- 18].
Second, we described a novel ensemble technique for causal orientation that combines decisions of individual causal orientation methods to provide a more powerful predictor of causal directionality.
Other causal orientation methods perform worse, and some methods (e.g., ANM-MML) consistently prefer wrong decisions and have AUCs lower than 0.5.
In general, the other causal orientation methods perform worse, and some methods (e.g., ANM-MML) consistently prefer wrong decisions and have accuracies lower than 0.5.
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