Sentence examples for performance classifying from inspiring English sources

We also performed a more systematic analysis of tracking performance, classifying 1000 frames randomly selected from 24 male/female videos and likewise 1000 frames randomly selected from 37 female/female videos.

The OL dictionary, with the highest performance classifying individual movie reviews of the 6 dictionaries tested in detail, performs worse than guessing at classifying individual sentences in movie reviews.

This CpG loci set showed excellent performance, classifying 47 of 49 low β and 13 of 13 high β tumor samples correctly for an overall success rate of 97%.

The method gave very high performance classifying, with the best set of features, provided by the two parameters of the new model, 93.3% of the examined subjects in agreement with the preclassification, provided by percentage difference of sway between eyes open and eyes closed conditions and computed over the area of the 95% confidence ellipse.

On the basis of the Cut-off scores of a Brief Neuropsychological Battery (NBACE, a subtest of the Wechsler Memory Scale III) [ 14], impaired delayed verbal recall for which recognition testing does not improve performance classifies patients with amnesic MCI as having an "encoding/storage" pattern of memory loss.

Moreover, SVMs can be generated so as to minimize the impact of false positives, that is, unfeasible performances classified as feasible.

Specifically, we create supervised learning models and evaluate their performance on classifying students as low, moderate, or high performers.

For each analysis, we used a greedy forward search algorithm to select subsets of potential biomarkers, build NB classifiers (see below), and scored their performance for classifying lung cancer and controls using the training set.

The unlabeled data samples are used to test the performance of semi-supervised classification, while the testing sample set is used to test the performance of classifying the new data samples with the learned projection matrix.

In comparison with the SVMRFE method, the GLGS feature selection method delivered a comparable and/or better performance in classifying microarray data; however, our experimental results showed that it does not perform as well as SVMRFE in classifying MALDI-MS data.

The ranking metric utilised in this work evaluates MMM and SMM performance (on classifying multi-label compounds) equitably.