matlab的xgboost代码

以下是一个简单的XGBoost的Matlab代码示例，用于二元分类任务：

% 导入数据
data = readtable('data.csv');
X = table2array(data(:,1:end-1));
Y = table2array(data(:,end));

% 划分训练集和测试集
cv = cvpartition(size(X,1),'HoldOut',0.3);
X_train = X(cv.training,:);
Y_train = Y(cv.training,:);
X_test = X(cv.test,:);
Y_test = Y(cv.test,:);

% 定义XGBoost参数
param.num_class = 2;
param.max_depth = 6;
param.eta = 0.1;
param.gamma = 1;
param.min_child_weight = 1;
param.subsample = 0.8;
param.colsample_bytree = 0.8;
param.scale_pos_weight = sum(Y_train==0)/sum(Y_train==1);

% 训练模型
dtrain = xgb.DMatrix(X_train,Y_train);
xgb_model = xgb.train(param,dtrain);

% 预测测试集
dtest = xgb.DMatrix(X_test);
Y_pred = xgb_model.predict(dtest);

% 计算准确率
accuracy = sum(Y_pred==Y_test)/length(Y_test)

请注意，要运行此代码，您需要在Matlab中安装XGBoost包。您可以使用以下命令在Matlab中安装XGBoost：

!git clone --recursive https://github.com/dmlc/xgboost
cd xgboost
make
cd matlab
addpath(pwd)
savepath

然后，您可以使用以下命令在Matlab中加载XGBoost：

addpath('/path/to/xgboost/matlab')