Sentence examples for samples in our algorithm from inspiring English sources

In this sense, the predictions of the labeled samples in our algorithm are a tradeoff between the given class labels and the predictions of local homogeneous neighbors.

In our algorithm, each blood sample is tested serially with two EIA tests that should be highly sensitive and have different detection formats.

Despite the reduction in training samples, our algorithm still maintained its improvements with median AUC improvements well above 0.05.

Remarkably, without any prior knowledge about the number of cell types in the samples, our algorithm automatically separated different cell types into different modules, with a few exceptions.

In line with this previous study, the full peak series of the four surfactants SPAC, STAC, C12-AES and PEG were consistently recovered in all ten STP samples by our algorithm.

It is anticipated that the prediction accuracy delivered by our proposed approach will continue to improve as the number of TF-DNA complexes deposited in the PDB continues to grow which will increase the number of training samples for use in our learning algorithm.

One is the effective Gabor feature selection and the other is the number of hardest-to-classify samples in RDAB algorithm.

This contribution significantly improves the existing results by reducing the number of required samples in the randomized algorithm.

s(0) is the standard deviation in the predicted concentration for three different background blank samples, in the algorithms.

This procedure is very similar to the conformation sampling algorithm in our CRF method (Zhao et al., 2008, 2009).

In Section 2, we describe our algorithm, in which MC sampling is stopped either according to the sequential MC stopping rule or when we reach a given multiple testing significance threshold.