Sentence examples for features a large set of from inspiring English sources

Conventional QSPkR modeling methods for predicting Vss normally use, as features, a large set of physicochemical or molecular descriptors, most of which are calculated by specialized software.

The Exploit Guard features a large set of intrusion rules and policies and Microsoft says that this feature should now help protect organizations better against quite a few advanced threats, including zero day exploits.

Due to the importance of this kind of features, a large set of fitting methods have been suggested, as, for example, in [18, 29 31], to compute ellipse equations from data point sets.

The exterior features a large set of stairs that leads from the street level to the main entrance on the second floor.

In fact, long-living flies, when compared to control, featured a large set of nontargeted metabolites that increase at higher levels.

The plugin NetworkAnalyzer (Assenov et al., 2008; Doncheva et al., 2012b) and the Java application CentiBiN (Junker et al., 2006) feature a large set of centrality measures, but they cannot compute the measures for a user-defined set of seed nodes or for weighted networks.

GerDa is denoted as a multilayer artificial neural network with many hidden layers and millions of free parameters learning discriminant features among a large set of acoustic features.

To this end, we pre-processed the 74 datasets to minimize confounding biases and then used stepwise regression to identify the most informative features from a large set of potential targeting features.

Here, we introduce Differential Feature Index (DFI) to identify distinctive features across a large set of diverse experiments using read counts without any direct inter-sample normalization.

A straightforward and quick procedure is used to select a small number of variables as features from a large set of variables which are normally available in power systems.

To deal with the variant and unpredictable wireless signals, the positioning is casted in a four-layer Deep Neural Network (DNN) structure pre-trained by Stacked Denoising Autoencoder (SDA) that is capable of learning reliable features from a large set of noisy samples and avoids hand-engineering.