重写这段代码，但完成相同的功能，尽量让人看不出来重写的代码和原先代码是一样的

好，以下是重写后的代码，仍然针对 MNIST 手写数字数据集进行朴素贝叶斯分类器的训练和测试，但实现方式有所不同。新代码将训练和测试数据加载进来，以及将图像转换为向量的功能合并为一个函数，使用 fitcnb 函数训练朴素贝叶斯分类器并进行测试，最后输出测试结果的准确率和可视化结果。

function [acc] = nb_classification()
    % 加载 MNIST 数据
    mnist = loadMNIST();
    train_images = mnist.train_images;
    train_labels = mnist.train_labels;
    test_images = mnist.test_images;
    test_labels = mnist.test_labels;
    
    % 训练数据和测试数据的数量
    train_num = 600;
    test_num = 200;
    
    % 将图像转换为向量
    data_train = reshape(train_images(:,:,1:train_num),[],train_num)';
    data_test = reshape(test_images(:,:,1:test_num),[],test_num)';
    
    % 训练朴素贝叶斯分类器
    Mdl = fitcnb(data_train,train_labels(1:train_num));
    
    % 测试结果
    result = predict(Mdl,data_test);
    acc = sum(result==test_labels(1:test_num))/test_num;
    
    % 可视化结果
    xlabel = [0:9];
    resultbar = histcounts(result,xlabel+0.5);
    testbar = histcounts(test_labels(1:test_num),xlabel+0.5);
    bar(xlabel, [resultbar' testbar']);
    title(['精确度为：',num2str(acc*100),'%']);
end

function [mnist] = loadMNIST()
    % 加载 MNIST 数据
    mnist = struct();
    mnist.train_images = loadMNISTImages('train-images-idx3-ubyte');
    mnist.train_labels = loadMNISTLabels('train-labels-idx1-ubyte');
    mnist.test_images = loadMNISTImages('t10k-images-idx3-ubyte');
    mnist.test_labels = loadMNISTLabels('t10k-labels-idx1-ubyte');
end

function [images] = loadMNISTImages(filename)
    % 读取 MNIST 图像数据
    fp = fopen(filename, 'rb');
    assert(fp ~= -1, ['Could not open ', filename, '']);
    magic = fread(fp, 1, 'int32', 0, 'ieee-be');
    assert(magic == 2051, ['Bad magic number in ', filename, '']);
    num_images = fread(fp, 1, 'int32', 0, 'ieee-be');
    num_rows = fread(fp, 1, 'int32', 0, 'ieee-be');
    num_cols = fread(fp, 1, 'int32', 0, 'ieee-be');
    images = fread(fp, inf, 'unsigned char');
    fclose(fp);
    images = reshape(images, num_cols, num_rows, num_images);
    images = permute(images,[2 1 3]);
    images = double(images)/255;
end

function [labels] = loadMNISTLabels(filename)
    % 读取 MNIST 标签数据
    fp = fopen(filename, 'rb');
    assert(fp ~= -1, ['Could not open ', filename, '']);
    magic = fread(fp, 1, 'int32', 0, 'ieee-be');
    assert(magic == 2049, ['Bad magic number in ', filename, '']);
    num_labels = fread(fp, 1, 'int32', 0, 'ieee-be');
    labels = fread(fp, inf, 'unsigned char');
    fclose(fp);
end