Sentence examples for driving classification from inspiring English sources

Differences in the endpoints driving classification were also observed between the RCD and NCD.

In the present analysis, pain impact severity seemed to be the most important parameter driving classification of a patient into the 2 best categories or the 3 worst categories.

For each RCD and NCD chemical, the following endpoints driving classification were determined and evaluated: corneal opacity (CO), iritis (IR), conjunctiva chemosis (CC), conjunctiva redness (CR), and days to clear.

Open image in new window Fig. 11 Accuracy of driving skill classification for segmented curve cases.

Feature extraction using PCA and driving skill classification using k-NN and SVM are explained in Sects.

In this paper, we use the leave-one-out method for evaluating the accuracy of the driving skill classification algorithms.

From these results, we can select curves with a smaller radius and a larger angular change to increase the accuracy of driving skill classification.

Open image in new window Fig. 13 Accuracy of driving skill classification of different radii of curves (angular change, IA = 90°) Open image in new window Fig. 14 Accuracy of driving skill classification with different radii of curves (angular change = 45°).

Thus, driver identification can be performed with high accuracy through driving behavior classification based only on raw data collected from in-vehicle sensors via the Controller Area Networks (CAN) system.

Together these analyses demonstrate that simple RT differences were not strongly driving the classification accuracies.

To determine which features were "driving" the classification, we evaluated random forests feature importance by mean decrease in Gini index (MDG; Figure 1b; see Methods).