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Pseudo code for feature ranking method.
Pseudo code for feature ranking method.
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Figshare
2017-02-03 更新
2026-04-29 收录
特征选择
机器学习特征工程
数据链接:
https://figshare.com/articles/dataset/Pseudo_code_for_feature_ranking_method_/4614886
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资源简介:
Pseudo code for feature ranking method.
应用场景:
创建时间:
2017-02-03
相关数据集
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。
github
2024-05-23 更新
15
0
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 Commons
2024-03-24 更新
7
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Regression coefficient was obtained by L1-penalized logistic regression (details are described in Material and Methods) and sorted by descending absolute values.
L1正则化
特征选择
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 Ecosystem
4
0
The highest classification accuracy of each algorithm on each data set and its feature subset length.
机器学习
特征选择
The highest classification accuracy of each algorithm on each data set and its feature subset length.
NIAID Data Ecosystem
8
0
The frequencies of features in the optimal feature subsets.
特征选择
特征重要性评估
The frequencies of features in the optimal feature subsets.
Figshare
2015-12-03 更新
4
0
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