用MATLAB鸢尾花数据集学习并且做聚类分析

% 加载原始数据 dataset = csvread('test_1.csv', 1, 0); % 加载train_1.csv数据集 trainData = csvread('train_1.csv', 1, 0); % 合并数据集 dataset = [dataset; trainData]; % 缺失值处理 means = mean(dataset, 'omitnan'); dataset(isnan(dataset)) = means(1); % 去除重复数据 dataset = unique(dataset, 'rows'); % 划分训练集和测试集 idx = crossvalind('HoldOut', size(dataset,1), 0.3); dataTrain = dataset(idx,:); dataTest = dataset(~idx,:); % 分离特征和标签 featuresTrain = dataTrain(:,1:4); labelsTrain = dataTrain(:,5); featuresTest = dataTest(:,1:4); labelsTest = dataTest(:,5); % 归一化处理 featuresTrainNorm = zscore(featuresTrain); featuresTestNorm = zscore(featuresTest); % 训练模型 model = fitcecoc(featuresTrainNorm, labelsTrain, 'Coding', 'onevsall', 'Learners', 'svm'); % 预测并评估模型 predictions = predict(model, featuresTestNorm); accuracy = sum(predictions == labelsTest) / numel(labelsTest); disp(['Accuracy:', num2str(accuracy)]);