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动手学深度学习房价预测练习
kaggle竞赛网址 kaggle california house prices
config.py
cpu
还是gpu
训练Adam
Dataloader
线程数dataset.py
数据处理分三个部分: 数据预处理/k折交叉取数据/数据加载
数据预处理
object
的数据去除掉nan
数据替换为0train_set/train_labels/test_set/test_id
test_id
主要用于test时填充test_id列k折交叉取数据
train_set/train_labels
分成k份valid_set/valid_labels
,其余部分作为真正的train_set/train_labels
数据加载
CHP_Dataset
和DataLoader
加载mini-batch大小的数据model.py
MLP
MSELoss
log_rmse
函数,为了与kaggle结果评估方式一致train.py
k折交叉验证训练,最终得到k个模型
test.py
选择k个模型中损失最小的模型进行推理
No Description
Python PowerShell CSV other
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