FS using CPCM

NIAID Data Ecosystem2026-03-10 收录

特征选择

机器学习预处理

数据链接：

https://data.mendeley.com/datasets/jnjgndrbc7 数据链接链接失效反馈

官方服务：

资源简介：

MATLAB code for feature selection using Conditional Priority Coverage Maximization (CPCM). The text file readme.txt has further details on the usage of the code.

创建时间：

2018-10-19

Straight line, 4D AND, 5D XOR, Hypersphere, Cone, Trigonometric, Double Spiral, Yin-yang, 5 multi-cut, 10 multi-cut

特征选择

数据集成

用于基准测试特征选择算法的合成数据集，包括多种类型的数据集，如直线、4D AND、5D XOR等，每个数据集都有其特定的特征和目标变量方程。

github2024-05-23 更新140

Machine Learning Feature Dimensionality Reduction Dataset

特征降维

机器学习预处理

Contains 12 datasets for feature selection dimensionality reduction and machine learning. The dimension of the selected datasets ranges from 10 to 1000, and the number of instances ranges from 20

IEEE30

Results of feature selection of the spambase dataset.

垃圾邮件检测

特征选择

Results of feature selection of the spambase dataset.

NIAID Data Ecosystem30

A method to distinguish between lysine acetylation and lysine ubiquitination with feature selection and analysis

蛋白质翻译后修饰

特征选择

Lysine acetylation and ubiquitination are two primary post-translational modifications (PTMs) in most eukaryotic proteins. Lysine residues are targets for both types of PTMs, resulting in different ce

DataCite Commons2024-03-24 更新70

Feature importance (Importance) and p values for features that achieved a feature importance greater than 0.1% in the Chinese RF.

特征选择

随机森林模型

Feature importance (Importance) and p values for features that achieved a feature importance greater than 0.1% in the Chinese RF.

NIAID Data Ecosystem30