Sentence examples for build a classifier based from inspiring English sources

We leverage the insights from this study to build a classifier based purely on static features to identify 92% of the remaining malicious singletons at a 1.4%percentt false positive rate, despite heavy use of obfuscation and packing techniques by most malicious singleton files that we make no attempt to de-obfuscate.

Our goals are first to identify distinguishing features for such urine excretory proteins and then to build a classifier based on these features to predict which proteins in cells can be excreted into urine.

The most frequently occurring value of parameter λ during the cross validation was used to build a classifier based on all training samples for independent testing.

Typically the analysis system will characterise the morphological features as well as the enhancement kinetics of the lesion (either using automated or manual lesion segmentation), then build a classifier based on those features that yield the highest diagnostic performance [ 27– 29].

We also built a classifier based on the adjective check-list scale (ACL) because this scale would be the most feasible one to be used in clinical setting.

PAM builds a classifier based on a ranking of CpG loci using a penalized t-statistic and then determines the misclassification error rate through 10-fold cross-validation.

We quantified the strength of the association and then built a classifier based on multi-variates Cox regression.

And then we built a classifier based on the selected features and applied the classifier to predict breast cancer from peripheral blood in an independent testing set.

We then built a classifier based on the combination of 17 cancer genes, gene expression predictors of smoking status, smoking history, and gender, plus patient age.

This study built a classifier based on grey matter in the posterior cingulate cortex, medial prefrontal cortex, and bilateral medial temporal lobes, which reached an accuracy around 90% in discriminating between the ASD and control groups.

For each drug, cancer cell lines that are either sensitive or resistant to the drug were included to build a chemoresponse classifier based on the 12-gene expression profiles in the cell lines.