机器学习 sklearn案列
时间: 2023-07-14 14:59:03 浏览: 47
好的,这里给你一个使用sklearn库进行分类的案例:
首先,我们需要导入相关的库:
```
import numpy as np
from sklearn.datasets import make_classification
from sklearn.model_selection import train_test_split
from sklearn.tree import DecisionTreeClassifier
from sklearn.metrics import accuracy_score
```
接下来,我们可以生成一些随机的数据来进行分类:
```
X, y = make_classification(n_samples=1000, n_features=10, n_classes=2, random_state=42)
```
将数据划分为训练集和测试集:
```
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.3, random_state=42)
```
使用决策树模型进行训练:
```
clf = DecisionTreeClassifier(random_state=42)
clf.fit(X_train, y_train)
```
预测测试集数据:
```
y_pred = clf.predict(X_test)
```
计算准确率:
```
accuracy = accuracy_score(y_test, y_pred)
print("Accuracy:", accuracy)
```
以上就是一个简单的使用sklearn库进行分类的案例。