Python XGBoost分类代码
时间: 2023-07-05 20:33:43 浏览: 76
好的,以下是一段使用XGBoost进行分类的Python代码示例:
```python
import xgboost as xgb
from sklearn.datasets import load_breast_cancer
from sklearn.model_selection import train_test_split
from sklearn.metrics import accuracy_score
# 加载乳腺癌数据集
data = load_breast_cancer()
X, y = data.data, data.target
# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
# 定义模型和参数
model = xgb.XGBClassifier(
max_depth=3,
learning_rate=0.1,
n_estimators=100,
objective='binary:logistic'
)
# 训练模型
model.fit(X_train, y_train)
# 在测试集上进行预测
y_pred = model.predict(X_test)
# 计算模型的准确率
accuracy = accuracy_score(y_test, y_pred)
print("Accuracy: %.2f%%" % (accuracy * 100.0))
```
这段代码使用XGBoost库加载乳腺癌数据集,划分训练集和测试集,定义XGBoost分类器模型并设置相关参数,训练模型并在测试集上进行预测,最后计算模型的准确率。