... functions have been shown to be very effective [22,24]. The ensemble of all HMM classifiers gave the best performance, given that the obvious diversity ... Selection For evaluating classifier combinations, another approach is to go through ...
... ensemble accuracy can also be used as the objective function. Finally, this investigation can be extended to regression problems, in which the exact Ambiguity decomposition includes a diversity ... selection from libraries of models. In ...
... diversity in majority vote ensem- bles. In: El Gayar, N., Kittler, J., Roli, F. (eds.) MCS 2010. LNCS, vol. 5997, pp ... Ensemble methods in machine learning. In: Kittler, J., Roli, F. (eds.) MCS 2000. LNCS, vol. 1857, pp. 1–15 ...
... Compound diversity functions for ensemble selection. Int. J. Patt. Recogn. Art. Intell. 23, 659–686 (2009) 7. Krogh Vedelsby (1995) 8. Liu, C.-L., Marukawa, K.: Normalization ensemble for handwritten character recognition. In: Proc. 9th ...
... selection to be made from very large (~ 1 million compounds) fully enumerated libraries in as little as 2 hours (SG ... compound selection process that represents a candidate reactant by a pharmacophore key that covers an ensemble ...
... function terms, for example, energy score and contact score into a consensus scoring approach [161]. Supervised learning with algorithms including support vector machines, ensemble learning, and random forests [162] can be used to ...
... compounds from the screen against the crystal structure were prioritized for experimental evaluation. Another 56 compounds were selected based on their mean rank against the MD ensemble. For the compounds selected from the crystal ...
... diversity can be encouraged in the ensemble by starting the search in the hypothesis space from different points. Since back-propagation can lead to local optima, assigning different initial weights to the neural networks that compound ...
... ensemble docking and consensus scoring was conducted, as a means of correctly assessing the probability of a given ... functions are used [65]. Hence, we selected the docking software based on searching-algorithm capabilities and ...
... ensemble is formed by drawing one classifier from each cluster [25]. The dependence measure is the rate of double fault, also called compound ... selection is very similar to that of feature selection. On defining an evaluation criterion ...