For each gold standard, Table 9 compares the AUC achieved by the best individual causal orientation method to the AUC achieved by the ensemble method, which combines the predictions of all 11 methods using a logistic regression model.
Recently, the ensemble methods were also developed by researchers to extract the unique features of single models to enhance the forecast model performances.
(5) The ensemble method is developed by integrating 20 subclassifiers trained by 20 subdatasets based on 10-fold cross validation.
To deal with the data imbalance problem, the ensemble method is developed by integrating the 20 subclassifiers trained by 20 subdatasets.
The Ensemble method (EM) is one of the more popular aggregate morphology characterization techniques used by researchers [ 239, 253– 253].
The ensemble method was found to be more accurate than any individual causal orientation method.
The electron statistics and capacitance of metal nanoparticles are investigated by the Gibbs ensemble method.
Similar to the molten core dynamics for proline isomerase, the structure ensembles generated by the ensemble refinement method revealed specific core dynamics for HIV protease, in particular a conformational exchange that is likely functionally relevant.
The gene orthology predictions were generated by the Ensemble Gene Tree method [ 63], which is based on the PHYML algorithm for multiple protein sequence alignments, and uses MUSCLE for each gene family that contains sequences from all five species (A. sinensis, A. gambiae, Ae. aegypti, C. quinquefasciatus and D. melanogaster).
Single-molecule techniques are ideally suited to directly monitor molecular fluctuations in multi-step reactions in real-time, without averaging out their inherent stochasticity (Weiss, 1999), and have provided important insights into the dynamics of transcription, unattainable by conventional ensemble methods (Bai et al., 2006).
