我在数据集上运行knn方法后尝试计算准确率，但其输出中没有显示准确率指标。我该如何修复这个问题以便在其计算指标中显示准确率？感谢您的考虑。
这是我的代码：
!pip install sklearn!pip uninstall pandas!pip install pandas==1.2.0import pandas as pdimport mathimport numpy as npimport matplotlib.pyplot as pltfrom google.colab import filesfrom sklearn.model_selection import train_test_splitfrom sklearn.preprocessing import StandardScalerfrom sklearn.neighbors import KNeighborsClassifierfrom sklearn.metrics import classification_report, confusion_matrix#-----------------read file---------------------------uploaded = files.upload()with open('dataset.csv', 'r') as data: df3 = pd.read_csv(data , encoding = ('ansi')) df = pd.DataFrame(df3) print (df) df["TargetProId"]=df["TargetProId"].fillna("Unknown") #------new-------- del df['TaskState'] del df['Price']#----------------------preprocessing------------------#----------function definition------------------def string_to_int(s): ord3 = lambda x : '%.3d' % ord(x) return int(''.join(map(ord3, s)))id_cols = [k for k in df.columns if k.lower().endswith('id')]#id_cols.append('TaskState')df[id_cols] = df[id_cols].applymap(string_to_int)#----------------------set data------------------------x = df.iloc[:,0:10]y = df.iloc[:,11]X_train, X_test, y_train, y_test = train_test_split(x, y, test_size=0.3)print(X_train.shape, y_train.shape)print(X_test.shape, y_test.shape)#-------------------------normalize--------------------scaler = StandardScaler()scaler.fit(X_train)X_train = scaler.transform(X_train)X_test = scaler.transform(X_test)#-----------------------------knn-----------------------classifier = KNeighborsClassifier(n_neighbors=math.floor(math.sqrt(24855)))classifier.fit(X_train, y_train)y_pred = classifier.predict(X_test)#-------------------------result------------------------print(confusion_matrix(y_test, y_pred))print(classification_report(y_test, y_pred))回答：
您可以使用以下代码来计算准确率：
from sklearn.metrics import accuracy_scoreaccuracy = accuracy_score(y_test, y_pred)