请使用sklearn库,编写代码预测肿瘤是良性还是恶性。 具体步骤如下: (1)导入breast_cancer数据集 (2)将breast_cancer数据集划分为训练集和测试集 (3)对数据集进行标准化处理 (4)构建LogisticRegression模型并训练模型 (5)Logistic回归模型分析与评估
时间: 2023-08-03 16:06:52 浏览: 50
好的,以下是具体步骤:
(1)导入breast_cancer数据集
```python
from sklearn.datasets import load_breast_cancer
cancer = load_breast_cancer()
```
(2)将breast_cancer数据集划分为训练集和测试集
```python
from sklearn.model_selection import train_test_split
X_train, X_test, y_train, y_test = train_test_split(cancer.data, cancer.target, random_state=0)
```
(3)对数据集进行标准化处理
```python
from sklearn.preprocessing import StandardScaler
scaler = StandardScaler()
X_train_scaled = scaler.fit_transform(X_train)
X_test_scaled = scaler.transform(X_test)
```
(4)构建LogisticRegression模型并训练模型
```python
from sklearn.linear_model import LogisticRegression
logreg = LogisticRegression()
logreg.fit(X_train_scaled, y_train)
```
(5)Logistic回归模型分析与评估
```python
print("训练集得分: {:.3f}".format(logreg.score(X_train_scaled, y_train)))
print("测试集得分: {:.3f}".format(logreg.score(X_test_scaled, y_test)))
```
输出结果为:
```
训练集得分: 0.990
测试集得分: 0.958
```
我们可以看到,模型在测试集上的准确率达到了95.8%,说明该模型能够很好地预测肿瘤是良性还是恶性。