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In designing the proposed classification method, each class of dataset is represented by a set of sub-graphs (components), and a new extension of the k-associated optimal graph algorithm is introduced in the training phase to combine the smaller components.
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Fig. 8 Quality of clusters for 3 classes of datasets.
Table 1 presents several representative genes that are highly overlapping between both classes of datasets, which include not only the aforementioned FOS, FOXO1, and TP63 but also certain other genes, such as APOD [20], IGF1 [21] and FOXM1 [22] that have also been shown to strongly correlate aging with cancer.
The negative class of this dataset was defined based on literature knowledge of treatment effects in humans and rodents.
The output layer contains 4 neurons, one for each class of the dataset.
Nearly 64% of the NSH class of CaEST dataset did not show any significant match thereby confirming that these ESTs represent unique chickpea sequences.
Figure 4 illustrates the protein domains classes distribution of dataset B (498 samples) in 3D kernel space with GDA model.
Our study is tailored towards researchers who desire a currently sparse higher-order class of simulated datasets that are more difficult to solve than existing data simulations.
This problem appears when the number of patterns that represents one of the classes of the dataset (usually the concept of interest) is much lower than in the remaining classes.
The mean of F-measure and QPI values were averaged over the eleven activity classes of the dataset.
Iterators allow for lazy generation of a much broader class of underlying sequential datasets, because they do not need to provide access to arbitrary elements of the underlying series.
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