2.利用SVM构建一个能对手写数字进行识别的分类器。(可以采用sklean中提供的手写字数据集)
时间: 2024-03-17 22:46:10 浏览: 13
好的,下面是利用SVM构建手写数字分类器的步骤:
1. 导入需要的库和数据集:
```python
import numpy as np
import pandas as pd
from sklearn.datasets import load_digits
```
2. 加载手写数字数据集,并对数据进行预处理:
```python
digits = load_digits()
X = digits.data
y = digits.target
```
3. 将数据集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(X, y, test_size=0.3, random_state=42)
```
4. 构建SVM分类器:
```python
from sklearn.svm import SVC
svm = SVC(kernel='linear', C=1, gamma='auto')
svm.fit(X_train, y_train)
```
5. 对测试集进行预测:
```python
y_pred = svm.predict(X_test)
```
6. 对模型进行评估:
```python
from sklearn.metrics import accuracy_score
accuracy = accuracy_score(y_test, y_pred)
print("Accuracy:", accuracy)
```
这样,您就可以利用SVM构建一个能对手写数字进行识别的分类器了。