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The performance of all methods depends on one or more meta-parameters.
We find that the accuracy of prediction using one-class methods depends on the features used and in some cases may be better than a two-class approach judged by our own and others' studies.
The reliability of such methods depends on the database of experience: one might say "this will certainly happen" (because it always does), or "will probably happen" (because it usually does), or "it may happen" (because it sometimes does).
Since one parameter of the methods depends on the passenger density, adaptive versions where the relevant parameter is adjusted automatically are also put forward.
Evidently the fate of these new text-entry methods depends on more than just ease of use.
Most data fusion methods depends on system behavior, which do not allow to easily deal with unknown systems.
In addition, the efficiency of seamless cloning methods depends on the intrinsic competency of E. coli cells.
However, success of these methods depends on assumptions and input parameters which must be representative for the rock mass.
The performance of the different methods depends on the type of bias of the model, and on the investigated statistic.
The suitability of indirect methods depends on the cost, accuracy, response time, effort involved in installation, management and durability of the equipment.
It is well known that the performance of these simulation based identification methods depends on the numerical approximations used in their design.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com