scikit-learn的kmeans对鸢尾花数据集的聚类效果很差怎么改进
```python
import numpy as np
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
from sklearn import datasets
from sklearn.datasets import load_iris
from sklearn.preprocessing import StandardScaler # 标准化工具
from sklearn.model_selection import train_test_split
iris = load_iris()
x_train, x_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.3,shuffle=True)
st = StandardScaler()
x_train = st.fit_transform(x_train)
x_test = st.transform(x_test)
est = KMeans(n_clusters=3)
est.fit(x_train,y_train)
y_predict = est.predict(x_test)
labels = ["山鸢尾", "虹膜锦葵", "变色鸢尾"]
score=0
for i in range(len(y_predict)):
print("%d: 真实值:%s \t预测值:%s" % ((i+1), labels[y_test[i]],labels[y_predict[i]]))
if labels[y_predict[i]]==labels[y_test[i]]:
score=score+1
est_score=score/len(y_predict)
print("准确率：", est_score)
```