logistic模型matlab代码

这是一个简单的逻辑回归模型的 MATLAB 代码：

% X is the input data, with each row representing a feature vector
% y is the label vector, with each element being either 1 or 0

% Initialize the weights randomly
weights = randn(size(X, 2), 1);

% Set the learning rate
learning_rate = 0.01;

% Number of iterations for gradient descent
num_iterations = 1000;

% Perform gradient descent
for i = 1:num_iterations
    % Compute the predicted probabilities
    predicted_probabilities = sigmoid(X * weights);
    
    % Compute the errors
    errors = y - predicted_probabilities;
    
    % Update the weights
    weights = weights + learning_rate * X' * errors;
end

% Define the sigmoid function
function p = sigmoid(z)
    p = 1 ./ (1 + exp(-z));
end

其中, X 是输入数据，每行表示一个特征向量，y 是标签向量，每个元素为 1 或 0。其中sigmoid是将输入转化为概率值,这里使用了梯度下降法来更新权重。

建议你进一步阅读相关文献了解模型的实现细节和参数调整。