Sentence examples for building a classifier using from inspiring English sources

According to standard procedure, building a classifier using machine learning is a fully automated process that follows the preparation of training data by a domain expert.

In high-dimensional applications, it is often desirable to build a classifier using only a subset of features due to the fact that (i) many of the features are not informative for classification and (ii) the number of training samples available for building the classifier is substantially smaller than the number of possible features.

We compared a classifier using domains against a classifier using either AAC monomers or AAC dimers as features.

In conclusion, we have demonstrated that a supervised machine learning approach to building a classifier for finding patients that might have FH using EHR data is feasible with a positive predictive value of 0.88, sensitivity of 0.75 and specificity of 0.99.

One-class uses only the information for the target class (positive class) building a classifier which is able to recognize the examples belonging to its target and rejecting others as outliers.

Several machine-learning algorithms were investigated in building a classifier to predict novel cancer genes, including naïve Bayes, logistic regression and support vector machines (SVM), all of which have been widely used for pattern classification and regression problems.

(ii)Building a classifier.

One of the major problems in building a classifier is the non-availability of labeled data.

al. use, in contrast to the one presented here, does not attempt to computationally and algorithmically highlight differences in phenotypes by building a classifier around measurable network features.

A necessary step when building a classifier for high-dimensional data is feature selection.

With such a limited data set, building a classifier is premature.