from sklearn.pipeline import Pipeline from sklearn.compose import ColumnTransformer from sklearn.preprocessing import StandardScaler, OneHotEncoder from sklearn.linear_model import LogisticRegression # 定义不同类型的特征列及其对应的预处理方法 numeric_features = [0, 1, 2] categorical_f...
auto import tqdm def train(model: torch.nn.Module, train_dataloader: torch.utils.data.DataLoader, test_dataloader: torch.utils.data.DataLoader, optimizer: torch.optim.Optimizer, loss_fn: torch.nn.Module = nn.CrossEntropyLoss(), epochs: int = 5): # 2. 创造空字典储存结果 results = {"...