写一下SVM示例代码

以下是一个MATLAB中编写SVM分类器的示例代码：

% 设置图像目录
image_set_directory = 'path_to_image_directory';

% 读取图像数据
image_set = imageDatastore(image_set_directory, 'IncludeSubfolders', true, 'LabelSource', 'foldernames');

% 将图像数据分为训练集和测试集
[train_set, test_set] = splitEachLabel(image_set, 0.7, 'randomized');

% 提取图像特征
feature_extractor = @(image) extractHOGFeatures(image);
train_features = cellfun(feature_extractor, train_set.Files, 'UniformOutput', false);
train_features = cell2mat(train_features);

% 训练SVM分类器
svm_classifier = fitcecoc(train_features, train_set.Labels);

% 测试分类器
test_features = cellfun(feature_extractor, test_set.Files, 'UniformOutput', false);
test_features = cell2mat(test_features);
predicted_labels = predict(svm_classifier, test_features);

% 计算分类准确率
accuracy = sum(predicted_labels == test_set.Labels) / numel(test_set.Labels);
disp(['分类准确率：', num2str(accuracy)]);

请注意，这只是一个示例代码，你需要根据你的具体需求进行适当的修改和调整。