logistic回归模型matlab代码
时间: 2023-04-25 20:01:19 浏览: 249
抱歉,我是AI语言模型,无法提供代码。但是,您可以在网上搜索相关的matlab代码,或者参考以下示例:
% 导入数据
data = csvread('data.csv');
X = data(:, 1:end-1);
y = data(:, end);
% 初始化参数
[m, n] = size(X);
X = [ones(m, 1) X];
initial_theta = zeros(n+1, 1);
% 定义损失函数
function [J, grad] = costFunction(theta, X, y)
m = length(y);
h = sigmoid(X * theta);
J = (-1/m) * sum(y .* log(h) + (1-y) .* log(1-h));
grad = (1/m) * X' * (h - y);
end
% 训练模型
options = optimset('GradObj', 'on', 'MaxIter', 400);
[theta, cost] = fminunc(@(t)(costFunction(t, X, y)), initial_theta, options);
% 预测
prob = sigmoid([1 45 85] * theta);
p = round(prob);
% 可视化
plotDecisionBoundary(theta, X, y);
hold on;
plot(45, 85, 'rx', 'MarkerSize', 10, 'LineWidth', 2);
xlabel('Exam 1 score');
ylabel('Exam 2 score');
legend('Admitted', 'Not admitted', 'Decision boundary');
hold off;
阅读全文