Sentence examples for instance selection method from inspiring English sources

It uses meta-learning to select the best suited instance selection method for each specific database, among several methods available.

The taxonomy allows discrimination among a large number of methods which pre-existing taxonomies for offline instance selection methods did not distinguish.

In addition, in contrast to most of the existing methods, which applied instance selection to classification tasks (discrete prediction), the proposed approach is used to obtain instance selection methods for regression tasks (prediction of continuous values).

In this context, it is envisaged to use, for instance, feature selection methods in order to select subsets of attributes for the individual classifiers.

This paper presents a refined taxonomy of instance selection and generation methods for the classification of data streams subject to concept drift.

The next step is to apply a clustering based sample selection method to select related instances as new training data, which resolves the marginal distribution differences in the latent input space.

The authors define inclusion criteria; The authors define an adequate selection method (for instance, all hospitalized patients with infection); The selection of participants was consecutive; The outcome data was complete (microbiology data by place of acquisition) and reported (no attrition bias); All results were reported (reporting bias).

In this paper, a new method called Random Subspace Instance Selection (RSIS) is proposed for the robust design of MIL ensembles without any prior assumptions on the data structure and the proportion of instances in bags.

Our proposed method can be applied after performing feature selection and instance selection to reduce their dimensionalities and data samples, respectively.

A forward selection method was chosen over a backward selection method in this instance because of the large number of potential covariates (candidate genes).

RF is a multivariate correlation-based feature selection method that compares feature values of the k nearest instances for the same and the other classes [ 37].