Sentence examples for the classification prediction from inspiring English sources

To the best of our knowledge, the SVM model developed in this work is the first one for the classification prediction of TACE inhibitors with a broad applicability domain.

Next, the classification (prediction) model was applied on the test set containing the remaining 18 breast cancer cell lines to predict the sensitivity or response of these 18 breast cancer cell lines to each drug compound.

The classification prediction (whether an unseen example is classified as belonging to the intelligible or unintelligible class), is achieved by summing the activation values at each voxel multiplied by their associated weight value, and adding a bias term.

However, the same cannot be said about MMM because in this case the classification predictions can be partially correct, fully correct or fully wrong.

In the ensemble technique, the scheme employed in this work, the classification of a new pattern x is typically made through majority voting of the classification predictions of j >1) single (or base) classifiers.

Because of the apparent similarities in classifying contigs between each method, we used the Spearman non-parametric test to determine if there was a significant correlation between the classification predictions of each methodology.

Logistic regression analysis was performed to examine the impact of age at diagnosis, tumor size and grade on the classification predictions and considered significant if the P-value was ≤0.05.

Considering the general performance of the classification-prediction, it can be seen that the prediction either fits or overestimates the known/observed number of triggered landslides for a series of earthquakes, while it often underestimates the size of the affected area.

The consensus classification prediction was based on the majority vote across the five structures for each molecule.

This may be problematic, as patients with a high risk of readmission may be assigned the same classification prediction as those whose readmission risk is considerably lower.

SNRs have been shown to provide one of the most accurate classification prediction methods (Cho and Ryu 2002).