Sentence examples for dimensions of vectors from inspiring English sources

Figure 15 depicts parallel processing of n dimensions of vectors p and q using DFEs.

A growing number of studies indicate ENM is a useful tool for understanding ecological and geographic dimensions of vectors and disease reservoirs [19] [27] and for identifying areas that may become affected under future climates, causing public health problems [28] [32].

The SVM-based classifier has been developed using 20 dimensions of vector, one for each amino acid.

We generated a total of 405 dimensions of vector by using 400 features of dipeptide composition and 5 features of the selected five domains of PROSITE.

In the hybrid approach, we generated a total of 19 dimensions of vector by using 14 features of selected dipeptides and 5 features of PROSITE domains.

The dipeptide composition was used to encapsulate the global information about each protein sequence, which gives a fixed length pattern of 400 (20 × 20) dimensions of vector.

An SVM-based classifier has been developed, using four dimensions of vector, one for each domain; this achieved 61.41% sensitivity, 90.65% specificity, 76.08% accuracy and 0.54 MCC.

In the hybrid approach, we combined 14 selected dipeptides with 5 PROSITE domain features and created total 19 dimensions of vector.

In the hybrid approach, we combined 18 selected dipeptides with 4 PROSITE domain features and created total 22 dimensions of vector (figure 8).

Total length of input of SVM is increased by four; now there are a total of 24 dimensions of vector for hybrid approach1 [amino acid and PROSITE] and 404 for the all dipeptide composition and PROSITE.

An SVM-based classifier was developed using 400 dimensions of vector (20 × 20) of dipeptide compositions, one for each dipeptide and this achieved 93.99% sensitivity, 62.43% specificity, 78.20% accuracy and 0.60 MCC.