基于lstm的开盘价收盘价预测实战 完整代码数据详细教程

import numpy as np
import pandas as pd

import os
import matplotlib.pyplot as plt
import datetime as dt

from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Dropout, LSTM
from tensorflow.keras.callbacks import ModelCheckpoint, EarlyStopping

data=pd.read_csv('/home/mw/input/alibaba8326/BABA.csv')
data[0:3]

n=len(data)
train_data=data[(n//20)*14:(n//20)*19]
test_data=data[(n//20)*19:]

plt.plot(train_data['Open'], label='Train')
plt.plot(test_data['Open'], label='Test')
plt.legend()

scaler = MinMaxScaler(feature_range=(0,1))
scaled_data = sc