Sentence examples for achieving classification from inspiring English sources

LSFT enhanced the performance of the PNN, achieving classification accuracies of 95.24% for discriminating between metastatic and primary tumors and 93.48% for distinguishing gliomas from meningiomas.

In experiments with medium and large datasets, the H-LSVM reduces the prediction cost considerably while achieving classification results closer to the non-linear SVM than that of the linear case.

Yunhui et al. [82]: To study the problem of achieving classification accuracy at the cost of complexity of algorithm, a cascaded weak classifier composed of several weak classifiers (based on extended Haar rectangle features) has been compared with KNN, NN-BP and SVM for cold-rolled strips.

With this approach, the achieved classification results are satisfactory.

For this case study, the proposed DSS achieved classification accuracies in a range from 76.1%to93.5%5% for different scenarios.

We have achieved classification accuracy of up to 97% for differential diagnosis of PD with confidence interval of 99.9%.

The achieved classification performance was 100%, 93.75% and 90.63% in the training, validation and testing set, respectively.

Experimental results showed that a reduced number of features can achieve classification accuracy superior than that using the full set of features.

The results show that a reduced number of features can achieve classification accuracy superior to that using the full set of features.

This study achieved classification accuracy of 95.1 ± 1.9%% using SVM classifier with features of time and frequency domains for five voluntary tongue motions and saliva swallowing.

Our method achieved classification rates of 99.04% and 98.30% on the Kondate (written in Japanese) and IAMonDo (written in English) heterogeneous document databases.