Sentence examples for classification setup from inspiring English sources

Towards handling larger HTS assays and exploiting the set of common active interactions as a factor for improving classification performance, we explore formulating the problem as a multi-label classification (MLC) instead of the conventional binary classification setup.

Lin et al. (2008) also pointed out some possible methodological flaws in the classification setup of Baranzini et al. (2005), which resulted in overly optimistic prediction accuracy values in the original paper.

The best classification setups are DT + FS, DT + BS, DT + SFFS.

In the summary section, the average classification accuracies are calculated based on LR, DT and SVM classification setups.

In addition to the ROC curve analysis which is used to evaluate the performance of best classification setups.

The confusion matrices for LR, DT and SVM based classification setups and weighted classification accuracies are reported in Tables 3, 5 and 6.

The confusion matrices of LR, DT and SVM based classification setups and weighted classification accuracies are provided in Tables 11, 12 and 13.

It was decided to develop online cardiac chest pain prognostic models based on LR based classification setups which are shown in Table 15.

In order to quantify performances of the best classification setups, the Receiver Operating Characteristic (ROC) curves are used as shown in Fig. 3 (evaluating the underlying area), which compare the specificity and sensitivity of experimental setups.

The performance complexity trade-offs in this case could be considered to limit the amount of tests (by focussing on the most significant tests picked up in the classification setups), needed to diagnose a patient with cardiac chest pain.

The experimental results reported in confusion matrices show that the LR + BS, DT + FS and SVM + SFFS are the best classification setups given the imbalanced nature of the patient dataset.