Simulated dataset

doi:doi:10.57702/x6zsx4po

Simulated dataset

The dataset used in this paper is a simulated dataset with 200 variables and 50 observations. The variables are generated from a multivariate normal distribution with a covariance matrix that has different correlation structures for active and inactive variables.

BibTex:

@dataset{Chen_Rui_and_Guo_Youwei_and_Zheng_Huafei_and_Jiang_Hongyu_2024,
    abstract = {The dataset used in this paper is a simulated dataset with 200 variables and 50 observations. The variables are generated from a multivariate normal distribution with a covariance matrix that has different correlation structures for active and inactive variables.},
    author = {Chen Rui and Guo Youwei and Zheng Huafei and Jiang Hongyu},
    doi = {10.57702/x6zsx4po},
    institution = {No Organization},
    keyword = {'Bootstrap', 'Gaussian', 'Machine learning', 'Neural networks', 'Non-Gaussian', 'Object Detection', 'Online Optimization', 'Promotions Personalization', 'Selection bias', 'Simulated data', 'Simulation Dataset', 'Staged trees', 'Synthetic Data', 'UAV', 'high-dimensional', 'high-dimensional data', 'k-parents staged trees', 'simulated dataset', 'sparse regression', 'sparse-group boosting', 'variable clustering'},
    month = {dec},
    publisher = {TIB},
    title = {Simulated dataset},
    url = {https://service.tib.eu/ldmservice/dataset/simulated-dataset},
    year = {2024}
}