matlab实现关联维算法
时间: 2023-05-31 08:04:53 浏览: 45
关联维算法是一种基于信息熵的特征选择方法,用于从高维数据中选择最相关的特征子集。在MATLAB中,可以使用以下代码实现关联维算法:
1. 首先,加载数据并将其分为特征和标签:
load('data.mat');
X = data(:, 1:end-1);
y = data(:, end);
2. 定义关联维算法函数:
function [selected_feats, MI] = rel_ents(X, y, k)
% Compute mutual information between each feature and label
MI = zeros(1, size(X, 2));
for i = 1:size(X, 2)
MI(i) = mutualinfo(X(:,i), y);
end
% Select top k features with highest mutual information
[~, idx] = sort(MI, 'descend');
selected_feats = idx(1:k);
end
3. 调用函数并输出结果:
k = 5; % number of features to select
[selected_feats, MI] = rel_ents(X, y, k);
fprintf('Selected features: %s\n', mat2str(selected_feats));
fprintf('Mutual information: %s\n', mat2str(MI(selected_feats)));
输出结果将显示选定的特征和它们与标签的互信息。