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The healthy older adults and AD patients had lower performance than the young adults, and particularly for naming living things with a low number of features.
Exceptions are naive Bayes and diameter 0 and 2, which is due to the low number of features with low diameter.
In comparing the MT and FP datasets, because of the relatively low number of features, such exhaustive analysis could be carried out.
The low number of features is a bias of the forward selection.
The 3-nucleotide/position representation, thus, captures additional correlations between nucleotides, while maintaining a low number of features (specifically, 139 features for our sequences which have length 141), thereby making the two views comparable.
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One can observe that the proposed method achieved higher validation accuracy (0.81) than all other compared feature selection approaches, while using the lowest number of features in the final prediction model.
Although texture analysis based on local binary patterns could be performed for different values of P and R, to ensure minimum computational complexity and lowest number of feature descriptors, we kept our analysis limited to P = 8 and R = 1.
However, the success of such systems often relies on jointly utilizing information from different sources and features as recognizing personality based on a low number of extracted features often do not yield high accuracy.
This is due to the low number of selected features (1024), as shown below.
Moreover, the low number of key features present in the EAP group may very well have led to a reduced effectiveness of the EAP.
However, when comparing peptides from samples that are not closely related, the low number of common features might not allow confident peak alignment, as has been shown for primary tissues like cancer cells (Casado and Cutillas 2011).
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