Sentence examples for data classification accuracy from inspiring English sources

The study is carried out not only in terms of conventional efficiency metrics used in filtering (MSE) but also in terms of multichannel data classification accuracy (probability of correct classification, confusion matrix).

MDA performances for the test points from the electrophysiological data set indicate that eliminating the best neurons one by one to simulate an increase in the noise levels results in degradation of test data classification accuracy for all methods and that the sorted sequence of best performers is MDA>PCA>ANN>MGD (Figure 4A).

In the first evaluation of GLAD performance, test data classification accuracy was compared between models identified using only labeled data and models using both labeled and unlabeled data.

However, when using Landsat 7 ETM data, classification accuracies of water hyacinth were relatively lower (i.e. 67%), when compared to other land cover types (i.e. water with accuracy of 100%).

Similar classification performance was achieved using real-time PCR data compared to that of microarray data: the classification accuracy, sensitivity and specificity for the testing set based on TaqMan® assay data were 80 %, 71, and 100% respectively (Figure 4).

For imbalanced data, a classification accuracy can be calculated both for positive and negative classes independently.

Experiments are performed for muscle fatigue classification using surface electromyography data where classification accuracy is measured as the performance metric.

If we don't use the ellipsoidFN method to reduce the dimension of the data, the classification accuracy will be much lower.

Both the high influence miRNA and experimentally verified prostate miRNA lists performed equally well on the NCI60 data (91% classification accuracy), but high-influence miRNAs performed better than known prostate miRNAs on GSE23022 (87% and 77%, respectively).

As we expected, for the original miRNA expression profiling data, the classification accuracy of miRNAs group with 34 common miRNAs shared by two miRNAs interaction networks is up to 100% using four classifiers.

This trend proved that EPSO is suitable for selecting a small number of genes from high-dimensional data (gene expression data) to maximize classification accuracy.