% Data preparation data = readtable('Attrition_train.csv'); n = size(data, 1); train_ratio = 0.8; train_size = floor(n * train_ratio); train_indices = randsample(n, train_size); test_indices = setdiff(1:n, train_indices); train_data = data(train_indices, :); train_labels = data(train_indices, end); test_data = data(test_indices, :); test_labels = data(test_indices, end); % Model training k = 5; model = knnsearch(train_data(:, 1:end-1), train_labels, 'NumNeighbors', k); % Model test predictions = predict(model, test_data(:, 1:end-1)); accuracy = sum(predictions == test_labels) / length(test_labels); disp(['Accuracy: ', num2str(accuracy)]);报错：参数名称 NumNeighbors 无效。代码更改

根据MATLAB官方文档，`knnsearch`函数的第二个参数应该是查询点的坐标，而不是标签。所以，你需要将第二个参数从 `train_labels` 改为 `train_data(:, 1:end-1)`。同时，在 `knnsearch` 函数中，`NumNeighbors` 参数应该放在函数名之后，而不是放在参数列表中。最终的修改后代码如下所示：

% Data preparation
data = readtable('Attrition_train.csv');
n = size(data, 1);
train_ratio = 0.8;
train_size = floor(n * train_ratio);
train_indices = randsample(n, train_size);
test_indices = setdiff(1:n, train_indices);
train_data = data(train_indices, :);
train_labels = train_data.Attrition;
train_data = train_data(:, 1:end-1);
test_data = data(test_indices, :);
test_labels = test_data.Attrition;
test_data = test_data(:, 1:end-1);

% Model training
k = 5;
model = knnsearch(train_data, train_data, 'K', k);

% Model test
predictions = predict(model, test_data);
accuracy = sum(predictions == test_labels) / length(test_labels);
disp(['Accuracy: ', num2str(accuracy)]);

注意，我还对数据的读取和预处理部分进行了一些修改，以确保程序能够正确运行。