Sentence examples for multivariate features from inspiring English sources

Two main approaches have been used, which focus either on the amounts of variation or on covariance structures of multivariate features such as shape.

In order to identify multivariate features explaining potential modifications by EPO in the cell cultures, single sample analyses were performed first (see Additional file 1).

Filter approach is further classified into two categories [20] as univariate (ranking) and multivariate (feature subset).

Most of the existing approaches perform data classification based on a distance measure in a multivariate feature space.

To handle the problem of small ratio of samples to features, in this paper, we have also utilized three well-known multivariate feature selection methods viz.

Multivariate feature selection and/or deep learning could potentially be used to help stress these interconnections and remove features which are redundant.

To investigate the performance of different combinations of the two feature extraction and multivariate feature selection methods, experiments are performed on a publicly available EEG data [4].

3. Multivariate feature selection methods are included in Sect. 4. Description of experimental setup and results are discussed in Sect. 5. Finally, Sect.

A multivariate feature selection method based on wavelet transform and empirical mode decomposition is proposed in [11] for mental task classification.

The method proposed here is related to these, except that we propose a multivariate feature selection method and consider parameter estimation using a multivariate shrinkage technique.

To address this issue, multivariate feature selection algorithms from machine learning have been used in analyzing multi-voxel patterns of brain activation [13], [14], [15], [16], [17], [18].