Sentence examples for build a classification from inspiring English sources

For each subspace of the predictors, we build a classification tree or logistic regression tree.

This paper attempts to build a classification model according to the research products created by those institutes and hence to design specific evaluation processes.

Our technique, based on Classification Trees, uses the properties of known objects to build a classification analysis which provides the probability for an unidentified source to belong to a given astronomical class (Pulsar, AGN,...).

This paper tackles the sovereign credit rating classification problem within an ordinal classification perspective by employing a pairwise class distances projection to build a classification model based on standard regression techniques.

Recasting the classification task for the sentence level and reusing code from other text analysis projects allowed us to quickly build a classification system that performs with a system F-score of 92.64 based on held-out data tests and of 85.57 on the formal evaluation data.

We also performed a new classification of 584 kinases on the basis of the similarity score which allowed us to build a "classification tree" of the currently known kinases ATP cavities.

To solve the class prediction problem, we built a classification tree on the learning set, and then sought the optimal placement of each test sample within the classification tree.

Effectively this procedure builds a classification model with 90% of the spectra and then tests the remaining 10% to assess classification accuracy.

Furthermore, we built a classification model using logistic regression to assess the performance of the purine pathway analytes in separating the groups in space.

Model robustness was tested by cross-validation (CV) with Venetian Blinds, which builds a classification model based on 90% of the data, tests the remaining 10% against that model, and repeats the process through ten iterations to assess its predictive power.

The first concept separates all variables to groups according to prior knowledge and builds a classification model for each group independently.