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网站维护一般需要多久,毕业设计可以做网站吗,分销电商,俄文网站制作使用pytorch进行batch_size分批训练，并使用adam+lbfgs算法 数据探索 训练过程及结果 整批次训练与分批次训练对比 绘制结果对比曲线 绘制无序曲线对比结果图 使用pytorch神经网络进行波士顿房价预测 数据探索 训练过程及结果 import numpy as np import pandas as pd impor…使用pytorch进行batch_size分批训练，并使用adam+lbfgs算法数据探索训练过程及结果整批次训练与分批次训练对比绘制结果对比曲线绘制无序曲线对比结果图使用pytorch神经网络进行波士顿房价预测数据探索训练过程及结果importnumpyasnpimportpandasaspdimportmatplotlib.pyplotaspltfromsklearn.model_selectionimporttrain_test_splitfromsklearn.preprocessingimportStandardScalerimporttorchimporttorch.nnasnnimporttorch.optimasoptimfromtqdmimporttqdm url="https://raw.githubusercontent.com/Zhang-bingrui/Boston_house/refs/heads/main/house_data.csv"boston_df=pd.read_csv(url,header=0,on_bad_lines="skip"# 跳过格式错误的行，防止报错)X=boston_df.drop('MEDV',axis=1).values y=boston_df['MEDV'].values#划分训练集和测试集# Veriyi %20 test setine ve %80 eğitim setine bölelimX_train,X_test,y_train,y_test=train_test_split(X,y,test_size=0.3,random_state=42)#输入数据标准化scaler=StandardScaler()X_train_scaled=scaler.fit_transform(X_train)X_test_scaled=scaler.transform(X_test)#将数据转换为pytorch的TENSORX_train=torch.tensor(X_train_scaled,dtype=torch.float32)X_test=torch.tensor(X_test_scaled,dtype=torch.float32)y_train=torch.tensor(y_train,dtype=torch.float32).view(-1,1)y_test=torch.tensor(y_test,dtype=torch.float32).view(-1,1)#创建数据加载器train_dataset=TensorDataset(X_train,y_train)test_dataset=TensorDataset(X_test,y_test)train_loader=DataLoader(train_dataset,batch_size=64,shuffle=True)test_loader=DataLoader(test_dataset,batch_size=64,shuffle=False)# ANN modellerini tanımlayalımclassANN(nn.Module):def__init__(self,input_dim):super(ANN,self).__init__()self.fc1=nn.Linear(input_dim,64)self.fc2=nn.Linear(64,32)self.fc3=nn.Linear(32,1)defforward(self,x):x=torch.relu(self.fc1(x))x=torch.relu(self.fc2(x))x=self.fc3(x)returnx num_epochs=500switch_epoch=