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资源简介：
iris with ignored features Sepal.Width and Petal.Length
应用场景：
创建时间：
2019-04-09
相关数据集
Straight line, 4D AND, 5D XOR, Hypersphere, Cone, Trigonometric, Double Spiral, Yin-yang, 5 multi-cut, 10 multi-cut
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150
Regression coefficient was obtained by L1-penalized logistic regression (details are described in Material and Methods) and sorted by descending absolute values.
Elastic-net parameters alpha was set to 0.975 and lambda was estimated as 0.075. Coefficients were calculated with standardized variables (STDV = 1).
NIAID Data Ecosystem40
Code of fuzzy Bayes risk model
Introduction: This main idea of this code is selecting features with relative lower risk by using a fuzzy Bayes risk model. In Ref. [2], we proposed a fuzzy Bayes risk model for weight assignment in L
Mendeley Data2020-07-29 更新20
The highest classification accuracy of each algorithm on each data set and its feature subset length.
The highest classification accuracy of each algorithm on each data set and its feature subset length.
NIAID Data Ecosystem80
Hyperparameter optimization using 10-fold grid search CV for the filtered LMCH data dynamics with 80:20 partition with feature selection.
Hyperparameter optimization using 10-fold grid search CV for the filtered LMCH data dynamics with 80:20 partition with feature selection.
Figshare2024-05-16 更新40
