scientific article; zbMATH DE number 7255067

zbMath1498.68284MaRDI QIDQ4969076

Jessica Minnier, Miriam R. Elman, Xiaohui Chang, Dongseok Choi

Publication date: 5 October 2020

Full work available at URL: https://jmlr.csail.mit.edu/papers/v21/19-117.html

Title: zbMATH Open Web Interface contents unavailable due to conflicting licenses.

zbMATH Keywords

classificationasymptoticrandom foresthigh-dimensionalnoise accumulationtotal signal index

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Statistical aspects of big data and data science (62R07) Computational aspects of data analysis and big data (68T09)

Uses Software

• R
• LIBSVM
• e1071
• gbm
• randomForest
• GitHub

Cites Work

• Unnamed Item
• Greedy function approximation: A gradient boosting machine.
• High-dimensional classification using features annealed independence rules
• Additive logistic regression: a statistical view of boosting. (With discussion and a rejoinder by the authors)
• Support-vector networks
• Theoretical Measures of Relative Performance of Classifiers for High Dimensional Data with Small Sample Sizes
• Random forests

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