項目視頻講解：
CEEMDAN-Transformer時間序列預測實戰完整代碼數據_嗶哩嗶哩_bilibili
完整代碼：
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# 加載數據
data = pd.read_csv('data.csv')# 數據歸一化
scaler = MinMaxScaler()
data['price'] = scaler.fit_transform(data['price'].values.reshape(-1, 1))class TimeSeriesDataset(Dataset):def __in
)
