Sentence examples for classify the datasets from inspiring English sources

We classify the datasets into three categories – biological, collaboration, and device networks: YEAST (biological), GRQC, HEPTH (collaboration), POWER, and OREGON (device) as described in Table 1.

After the data weighting stage, three different classification algorithms that included the k-NN (k-Nearest Neighbour), RBF NN (Radial Basis Function Neural Network) and SVM (Support Vector Machine) classifying algorithms have been used to classify the datasets.

The second strategy is the dataset division which employs the principal component analysis (PCA) to classify the dataset into training and test sets that yields statistically significant and robust models.

The first step of machine learning classification involves selecting the best algorithm most suited to classifying the datasets.

We classified the datasets on the basis of the GC3 of coding sequences rather than the overall GC, because the GC3 contents of mammalian genes are known to exhibit strong correlation with the GC content of the genomic region, where the genes are located.

An information gain of one is only possible if the rule perfectly classifies the dataset, and an information gain of zero implies the rule is no better than random.

(B) To each recovered shape, we can then associate a pair ((r_{0}, r_{1})) describing the shape's spatial coherency and circularity and use this information to classify the original datasets.

We then use Strand to classify the malware dataset used in the Kaggle Microsoft Malware Classification Challenge (BIG 2015) [19].

A multiclass Laplacian-modified Naïve Bayesian classifier, as described by Nigsch et al. [7] and later implemented by Koutsoukas et al. [10] was implemented to classify the bioactivity dataset and to be able to predict targets for novel compounds.

The centroids associated with the groups were derived using the nearest shrunken centroids method and used to classify the training dataset samples.

Each candidate set of centroids formed in the previous step was applied to classify the training dataset in an attempt to validate the corresponding possible subtypes.