首页/数据集/Appendix A. Performance of six measures of variable importance.

Appendix A. Performance of six measures of variable importance.

Figshare2016-08-05 更新2026-04-29 收录

变量重要性

特征选择方法

数据链接：

https://figshare.com/articles/dataset/Appendix_A_Performance_of_six_measures_of_variable_importance_/3530552 数据链接链接失效反馈

官方服务：

资源简介：

Performance of six measures of variable importance.

应用场景：

创建时间：

2016-08-05

变量重要性

分层分析

File List Variable Importance Simulation.txt Variable Importance Simulation.sas hierpart.txt hierpart.sas Description "Variable Importance Simulation.sas" is a simulation to evaluate the relative impo

DataCite Commons2025-05-01 更新100

The quartile and mean values of AUC accuracies of ESVM-RFE, SVM-RFE and BIRF on the four microarray datasets.

基因表达分析

特征选择方法

The quartile and mean values of AUC accuracies of ESVM-RFE, SVM-RFE and BIRF on the four microarray datasets.

NIAID Data Ecosystem50

Comparison of the accuracy of full models (i.e. model 43 for hard90, and models 26 for hard70) with the most accurate models based various FS methods.

特征选择方法

模型比较

The differences between these comparisons based on the Mann-Whitney tests (n = 100 for each model).

NIAID Data Ecosystem40

Supplement 1. Source code for variable importance situations.

统计分析

变量重要性

DataCite Commons2020-09-03 更新80

Supplement 1. Source code for variable importance situations.

变量重要性

层次分析法

File List Variable Importance Simulation.txt Variable Importance Simulation.sas hierpart.txt hierpart.sas Description "Variable Importance Simulation.sas" is a simulation to evaluate

NIAID Data Ecosystem50

Appendix A. Performance of six measures of variable importance.

资源简介：

相关数据集