Abstract. Lasso-type variable selection has been demonstrated to be effective in handling high dimensional data. From the biological perspective, ...
Apr 7, 2016 · Although some work has considered the problem of correlation, the issue of discriminative ability resulting from sparsity has been overlooked.
Abstract: A novel decoding scheme for motor imagery (MI) brain computer interfaces (BCI's) is introduced based on the GFT concept. It considers the recorded ...
A discriminative Lasso in which sparsity and correlation are jointly considered is proposed in which the new method can select features that are correlated ...
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Nov 8, 2016 · Discriminative Lasso. Zhihong Zhang, Jianbing Xiahou, Zheng-Jian Bai, Edwin R. Hancock, Da Zhou, Sibao Chen, Liyan Chen. Computer Science.
Apr 16, 2019 · It estimates a representation model while accounting for discriminativeness between classes, thereby enabling accurate derivation of categorical ...
DFC was a discriminative approach implemented using adaptive LASSO logistic regression. The results revealed that DFC well captured cell-type-specific ...
The objective of DALASS is to simplify the interpretation of Fisher's discriminant function coefficients. The DALASS problem—discriminant analysis (DA) ...
Request PDF | Discriminative Lasso | Lasso-type variable selection has been demonstrated to be effective in handling high-dimensional data.
K. Georgiadis, N. Laskaris, S. Nikolopoulos, D. Α. Adamos and I. Kompatsiaris, “Using Discriminative Lasso to Detect a Graph Fourier Transform (GFT) ...