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However, when training set size is small, the performance of logistic regression is worse than bagging.
When the fin pitch is small, the performance of PCTES unit becomes better using large fin height and width.
It is also proved that by choosing the relaxation parameter sufficiently small, the performance of the resulting control strategy can be made arbitrarily close to the optimal one.
It can be observed that when Pav is small, the performance of these three methods have negligible difference, while when Pav is large, SPSA is slightly better than PO and POHPA.
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Furthermore, it is well known that if the distance between the most neighboring areas becomes smaller, the performance of the numerical weather prediction also becomes better.
Moreover, (B-A) or (widetilde{B}-widetilde{A}) are smaller, the performance of a biorthogonal wavelet transform may be better, i.e., the energy is amplified in some cases and decreased in other cases.
However, for feature sets of small dimensions, the performance of IGR decreases substantially (this result is discussed in [91]).
It is clear from these results that the effects of shadowing are very small on the performance of the detection schemes.
However, if the noise in the weights w i is qualitatively small enough, the performance of the weighted feature method can then improve on that of the above mean feature method.
The p-values from the matched-pair t-test are shown in Table3; although the values are not always small, the performance improvement of the probabilistic 2-mode based method seems meaningful.
In terms of low contrast sensitivity and small detail detectability the performance of both designs of CR system is similar to that of a modern film screen combination.
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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