Sentence examples for model that classified from inspiring English sources

Incorporating all 181 metabolic markers and all 110 genetic markers resulted in a discriminant model that classified only 49% of the RILs correctly, which corresponds to a random classifier.

Ortony et al. (1987) presented a sentiment model that classified mental states into three categories: affect-focal, behavior-focal, and cognition-focal (see Fig. 1).

These features were then used in a prediction model that classified each enzyme into its top EC class with an accuracy of 33.1%, which is an increase of 16.4% over random classification.

A rule based machine learning technique, BioHEL, was used to create a model that classified the samples into their relevant treatment groups by identifying those proteins that separated samples into their respective groups.

We first present a general overview of bio-inspired systems and the POE model that classifies bio-inspired machines along three axes.

In addition, you would want to see added value in the percentage of correct classification over a model that classifies the cases without the variables.

Using a variety of input variables and architecture parameters, they were able to develop a NN model that classifies well in training sets, but were unable to develop a model with substantial predictive ability.

The feature information thus extracted is fed to discriminant classifiers or hidden Markov models that classify it into FACS action units, the descriptive system to code fine-grained changes in facial expression.

The first group of learning techniques involves the development of models that classify siRNAs into discrete groups of more effective and less effective, based on their properties or features.

Other groups focused on tissue specific differences between cancer sites by building supervised models that classify samples according to their tissue of origin [ 10, 11] or by comparing cancer from multiple tissues with normal tissue [ 12].

To train models that classify a protein as a hub or a non-hub, the protein interaction data from the four species were combined into a single data set (90,164 interactions involving 2,069 hubs and 19,715 non-hubs).