使用sklearn库,训练一个logistic模型
时间: 2023-12-28 21:48:42 浏览: 28
好的,我了解你的要求。关于使用sklearn库训练一个logistic模型,可以按照以下步骤进行:
1. 导入sklearn库和需要的数据集
```
import sklearn
from sklearn.datasets import load_digits
```
2. 加载数据集并进行预处理
```
digits = load_digits()
X = digits.data
y = digits.target
# 特征缩放
X = X/255.0
```
3. 分割数据集为训练集和测试集
```
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
```
4. 训练模型并进行预测
```
from sklearn.linear_model import LogisticRegression
log_reg = LogisticRegression()
log_reg.fit(X_train, y_train)
y_pred = log_reg.predict(X_test)
```
5. 评估模型性能
```
from sklearn.metrics import accuracy_score
accuracy = accuracy_score(y_test, y_pred)
print("Accuracy: ", accuracy)
```
希望这个例子对你有用!