登录后查看消息通知
搜索
常见问题
消息
登录
首页
/
数据集
/
Ranking of feature screening methods for regression by the number of times each was in the top performing group.
Ranking of feature screening methods for regression by the number of times each was in the top performing group.
收藏
Figshare
2019-09-11 更新
2026-04-29 收录
特征选择方法
回归模型特征工程
数据链接:
https://figshare.com/articles/dataset/Ranking_of_feature_screening_methods_for_regression_by_the_number_of_times_each_was_in_the_top_performing_group_/9805988
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:
(larger numbers are better).
应用场景:
创建时间:
2019-09-11
相关数据集
The performance of the feature sets selected for the causal discovery experiments.
因果发现
特征选择方法
The performance of the feature sets selected for the causal discovery experiments.
Figshare
2018-11-20 更新
7
0
Performance of different feature selection methods over the cross-validation and independent tests.
特征选择方法
机器学习模型评估
Performance of different feature selection methods over the cross-validation and independent tests.
Figshare
2025-10-08 更新
4
0
Performance of SVM and NB classifiers using the features selected by FCBF and SS strategies.
特征选择方法
分类器性能评估
Performance of SVM and NB classifiers using the features selected by FCBF and SS strategies.
Figshare
2021-01-19 更新
3
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
Performance of different feature selection methods over the cross-validation and independent tests.
特征选择方法
机器学习模型
Performance of different feature selection methods over the cross-validation and independent tests.
NIAID Data Ecosystem
3
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