项目视频讲解：
CEEMDAN-Transformer时间序列预测实战完整代码数据_哔哩哔哩_bilibili
完整代码：
import pandas as pd
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import MinMaxScaler
import torch
import torch.nn as nn
from torch.utils.data import DataLoader, Dataset
from torch.optim import Adam
from tqdm import tqdm
from pyemd import CEEMDAN
from torch.nn import TransformerEncoder, TransformerEncoderLayer
import torch.nn.functional as F
import warnings
warnings.filterwarnings("ignore", message="Using a target size")
import openpyxl# 加载数据
data = pd.read_csv('data.csv')# 数据归一化
scaler = MinMaxScaler()
data['price'] = scaler.fit_transform(data['price'].values.reshape(-1, 1))class TimeSeriesDataset(Dataset):def __in
)
