Sentence examples for measures of classification from inspiring English sources

To evaluate the performance of the Kinect for motion analysis, we applied a motion detection method (Han et al. 2013) to motion capture datasets from a Kinect and a VICON, and compared the results of detection based on conventional measures of classification performances (i.e., accuracy, precision, and recall).

We consider other measures of classification performance, including sensitivity (SE) and specificity (SP) of a classifier.

Summary measures of classification for the model are based on the sample-splitting approach.

That is because it was not possible to determine how comparable the measures of classification probability were between LCA programs.

In Figure 10, we report the results of our experiments, using four measures of classification model performance averaged over the 100 replications.

The AUC summary measures of classification performance (Table 1) confirmed the general picture that, even though the group-level statistics were highly significant, individual classification was overall poor in Experiment one.

The ROC curve is a two-dimensional measure of classification performance and is widely used in biomedical applications to assess the performance of diagnostic tests.

Entropy was calculated as a measure of classification uncertainty, based on the per-object class membership estimations from the SVM algorithm.

In general, the kappa coefficient lies typically on a scale between 0 and 1, whereas the latter indicates complete agreement and is often multiplied by 100 to give a percentage measure of classification accuracy.

We additionally use the size of the area under ROC curve as a cutoff-independent quality measure of classification.

DP is the ratio of correctly classified trials relative to all trials, and is the most commonly used measure of classification accuracy.