新建题库11191215

def train model(self, X_train, y_train):

"""训练模型"""

self.model.______(X_train, y_train)

joblib.dump(self.model,' model.pk1')

return self.model

"""测试模型"""

y_pred= self. model._________(self. X_test)

report= classification report(self. ytest, y_pred)

return y_pred, report

"""分析测试结果并生成报告"""

cm = _______________(self. y_test, y_pred)

plt. figure(figsize = (8, 6))

sns. heatmap(cm, annot = True, format = 'd')

plt. savefig('confusion_matrix. png')

return error_analysis, cm

trainer = ModelTrainer()

X_train,y_train,X_test,y_test = trainer.maintain_datasets(' dataset. csv')

model = trainer. train_model(X_train, y_train)y_pred, test_report = trainer. ______()

error_df, confusion_mat = trainer.analyze_results(y_pred)

def_init_(self):

self. model= ______(random_state=42)

self.X_test, self.y_test= None, None

def test_product(self, X_test):

"""测试AI产品"""

y_pred= self. model. predict(X_test)

return y_pred

"""测试AI产品"""

y_pred= self.model.predict(X_test)

return y_pred

def analyze_results(self, y_pred):

"""分析测试结果并生成报告"""

report= __________________(self. y_test, y_pred)

accuracy= accuracy_score(self. y_test, y_pred)

return report, accuracy

”"”分析错误案例原因””"

errors= self.X_test[self.y_test !=y_pred].copy()

errors[' true_label']= self.y_test[self.y_test != y_pred]

errors[' pred_label']= y_pred[self.y_test != y_pred]”

#分析错误特征分布

error_analysis= errors.______()

error_analysis.to_csv('error_analysis_report. csv')

return errors, error_analysis

pipeline = ModelPipeline()

X_train, X_test, y_train, y_test = pipeline. maintain_datasets('data. csv')

pipeline.train_algorithm(X_train, y_train)

predictions = pipeline.test_product(X_test)

test_report,accuracy = pipeline.___________(predictions)

error_cases,analysis = pipeline.analyze_errors(predictions)↵