嗨，我是数据科学和 python 的新手，我正在尝试使用 pandas matplotlib 编写一个 knn 分类程序。我正在使用 spyder Ide ，每个执行情节都在不断变化。我很困惑，是正确的还是我做错了，
import numpy as np
from matplotlib import pyplot as plt
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.metrics import roc_curve, auc,accuracy_score
import pandas as pd
iris_predict={ 0:'Iris-setosa' ,1:'Iris-versicolor',2:'Iris-virginica'}
neighbors=list(range(1,30))
train_result= []
test_result = []
iris= pd.read_csv ('G:\\IMAGE-DATASETS\\iriscsv\\Iris.csv')
iris['iris_num']=[iris_class[i] for i in iris['Species']]
y=iris['iris_num']
X= iris.drop(['Id','Species'],axis=1)
x_train, x_test, y_train, y_test = train_test_split(X,iris.iris_num, test_size=0.25)
for i in neighbors :
knn= KNeighborsClassifier(n_neighbors=i,
weights='uniform',
algorithm='kd_tree',
leaf_size=30,
p=2,
metric='minkowski',
metric_params=None)
knn.fit(x_train,y_train)
train_pred = knn.predict(x_train)
train_result.append(accuracy_score(train_pred,y_train))
y_pred = knn.predict(x_test)
test_result.append(accuracy_score(y_pred,y_test))
#graph
iris_color_bar= np.array(['setosa', 'versicolor', 'virginica'], dtype='<U10')
fig= plt.figure(figsize=(10,10)) # plotting area
fig.clf() # to avoid previous figure overlap
plt.title('iris data')
plt.xlabel('p')
plt.ylabel('auc_score')
plt.plot(neighbors, test_result, c='r', label='test')
plt.plot(neighbors, train_result, c='b', label='train')
plt.legend()
#plt.scatter(x,y,c=y, cmap=plt.cm.get_cmap('Set1', 3), data=iris)
#formatter = plt.FuncFormatter(lambda i, *args:iris_color_bar[int( i)])
#plt.colorbar(ticks=[0, 1, 2],format=formatter)
plt.show()
我怎样才能保持我的情节固定，以便我得出一些结论？