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Performance of sparse learning methods in feature selection.

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2021-10-07

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

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

iris with ignored features Sepal.Width and Petal.Length

OpenML2019-04-09 更新20

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.

Figshare2024-05-16 更新40