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n_estimators(迭代次数) 在训练中,我们仅使用了来自stock_price和stock_list文件的可用特征。
原文链接:JPX Tokyo Stock Exchange Prediction | Kaggle CODE: 2nd place solutionwww.kaggle.com/code/uioiuioi/2nd-place-solution 我认为第二名的方案存在缺陷。确切地说,我认为notebook并没有按照原方案(已被作者删除)描述的方式进行特征工程。 例如,我对return_1month的理解是,收盘价的20个工作日回报是...
Am**旧爱 上传28.49MB 文件格式 rar lstm kaggle 标题中的“ny-stock-price-prediction-rnn-lstm-gru.rar”表明这是一个关于纽约股票价格预测的项目,其中使用了循环神经网络(RNN)、长短时记忆网络(LSTM)和门控循环单元(GRU)这三种深度学习模型。在金融领域,股票价格预测是一个典型的时序数据分析问题,它涉及到利用...
In the course of working on this project, we conducted a regression analysis on the stock price of apple between the years 1980 and 2021. For this particular study, we relied on the techniques of Linear, Poisson and lasso regressions, from which we derived the accompanying graphs. These ...
Google Stock Prices Prediction Using Deep Learning In this paper, we have used Kaggle data of google stock price from the year 2012 to 2016. To predict the stock price of the first two months of ... K Ullah,M Qasim - IEEE International Conference on System Engineering & Technology 被引量...
Dataset : https://www.kaggle.com/datasets/shreenidhihipparagi/google-stock-prediction Solution : https://github.com/Shubasarkar1999/BharatIntern/blob/main/Task_1%20Stock%20Price%20Prediction%20Using%20LSTM.ipynb Task 2 Problem statement : Titanic Classification : Algorithm which tells whether the ...
array(current_price).reshape(1,1) _ = session.run(sample_prediction,feed_dict=feed_dict) feed_dict = {} current_price = all_mid_data[w_i-1] feed_dict[sample_inputs] = np.array(current_price).reshape(1,1) # Make predictions for this many steps # Each prediction uses previous ...
原文档可以看这里:Stock Market Analysis + Prediction using LSTM | Kaggle In this notebook, we will discover and explore data from the stock market, particularly some technology stocks (Apple, Amazon, Google, and Microsoft). We will learn how to use yfinance to get stock information, and visual...
plt.title('Altaba Inc. Stock Price Prediction') plt.xlabel('Time') plt.ylabel('Actual Stock Price') plt.legend(loc='upper left', fontsize=8) plt.show() As you can see our model did quite handsomely. Let us also check the commonly used accuracy metrics to judge forecast results: ...