python数据分析聚类算法
时间: 2023-11-26 14:47:21 浏览: 42
以下是Python实现K-Means聚类算法的步骤:
1.导入数据并进行标准化
```python
import pandas as pd
inputfile = './Python数据分析与挖掘实战(第2版)/chapter5/demo/data/consumption_data.xls'
data = pd.read_excel(inputfile,index_col = 'Id')
data_zs = 1.0*(data - data.mean())/data.std()
```
2.构建模型,初始化聚类中心
```python
from sklearn.cluster import KMeans
k = 3 # 聚类簇的个数
model = KMeans(n_clusters = k, n_jobs = 4, max_iter = 500) # 建立模型对象
model.fit(data_zs) # 训练模型
```
3.查看聚类结果
```python
r = pd.concat([data_zs, pd.Series(model.labels_, index = data.index)], axis = 1) # 将聚类结果整合到原始数据中
r.columns = list(data.columns) + [u'聚类类别'] # 重命名表头
```
4.可视化聚类结果
```python
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = Axes3D(fig)
ax.scatter(r[u'Frequency'], r[u'Monetary'], r[u'Recency'], c = r[u'聚类类别'])
plt.show()
```