Sentence examples for supervised criterion from inspiring English sources

Then geometry and texture features are extracted for each suspicious MC, a mutual information-based supervised criterion is used to select important features, and PFCM is applied to cluster the samples into two clusters.

Then geometry and texture features are extracted for each suspicious MC, a mutual information-based supervised criterion is used to select important features, and then PFCM is applied to cluster the samples into two clusters.

We present in this article a comparative study of well-known supervised evaluation criteria that enable the quantification of the quality of contour detection algorithms.

Furthermore, in the literature, most of the supervised channel-shortening criteria formulations, such as MSSNR [10], MGSNR [11], min-ISI [12], MBR [13] and SINR-max [14], are mainly based on the combined channel-plus-equalizer IR expression and their optimum TEQs which are perceived as solutions of algebra linear equations.

- Supervised and semi-supervised training – We distinguish between supervised and semi-supervised training.

We compare our method with two supervised and unsupervised evaluation criteria on real-world social network datasets.

By supervised analysis using specific criteria (at least a 2.0-fold increase or a 50% decrease in EGFR-mutant cell lines relative to that of wild-type, P<0.05), 194 unique genes were identified that distinguished the EGFR-mutant cell lines from the –wild-type cell lines.

Enrolment of 80% of the population in the vaccinated group and 54% in the comparison group, who were also involved in OM-RCT with more restrictive inclusion criteria and supervised therapy, introduced selection bias against a positive vaccine effect.

Two criteria for invariant supervised texture segmentation based on multi-channel approaches are introduced.

Interested scientists may want to quantify, aggregate and visualize statistics of some criteria in the supervised area.

examples of the supervised methods are maximum margin criteria (MMC), maximum relevance minimum redundancy (mRMR) and linear discriminate analysis (LDA), (ii) the unsupervised technique, however, transform the existing features by rotating and projecting them onto a minimal number of axes without using the target labels.