登录后查看消息通知
搜索
常见问题
消息
登录
首页
/
数据集
/
AUC comparison results for different sampling techniques.
AUC comparison results for different sampling techniques.
收藏
Figshare
2022-11-29 更新
2026-04-28 收录
采样技术评估
分类模型性能
数据链接:
https://figshare.com/articles/dataset/AUC_comparison_results_for_different_sampling_techniques_/21642784
数据链接
链接失效反馈
官方服务:
问题咨询
购买咨询
在线客服
NEW
资源简介:
AUC comparison results for different sampling techniques.
应用场景:
创建时间:
2022-11-29
相关数据集
Test results for different features.
特征工程评估
分类模型性能
Summary of results for multiple feature types on optimal weighted F scores. (FNR = False Negative Rate, TPR = True Positive Rate, FPR = False Positive Rate, TNR = True Negative Rate).
NIAID Data Ecosystem
7
0
Optimal classification accuracy with filtered subsets and IFS.
特征优化
分类模型性能
Optimal classification accuracy with filtered subsets and IFS.
NIAID Data Ecosystem
6
0
: Results of classifications performed without any feature selection, with the proposed method, using only the pre-selection step (Spearman’s correlation analysis) or only the selection by RF algorithm (RF importance coefficients).
特征选择评估
分类模型性能
: Results of classifications performed without any feature selection, with the proposed method, using only the pre-selection step (Spearman’s correlation analysis) or only the selection by RF algorith
NIAID Data Ecosystem
4
0
The F1 score obtained by six feature selection methods.
特征选择方法
分类模型性能
(XLSX)
NIAID Data Ecosystem
6
0
Test set classification accuracies and percentage of label requests per episode.
主动学习
分类模型性能
Test set classification accuracies and percentage of label requests per episode.
NIAID Data Ecosystem
5
0
© 2023-2026 上海数据发展科技有限责任公司 版权所有
沪ICP备17003045号-15
沪公网安备31010402336585号
热门搜索
社区交流群
科研交流群
商业服务
数据资源
寻源服务
数据采集
标注服务
数据产品
代理销售
数据领域
凭证登记
数据产品
介绍推广