登录
首页 » Python » StockPricePrediction-master

StockPricePrediction-master

于 2019-06-18 发布 文件大小:7501KB
0 233
下载积分: 1 下载次数: 2

代码说明:

  python深度学习股票分析框架,就这么多了(python learning stock)

文件列表:

StockPricePrediction-master, 0 , 2019-03-27
StockPricePrediction-master\.gitignore, 804 , 2019-03-27
StockPricePrediction-master\Documents, 0 , 2019-03-27
StockPricePrediction-master\Documents\SMAIProjectAbstract.pdf, 102446 , 2019-03-27
StockPricePrediction-master\Documents\StockPricePrediction.pdf, 665338 , 2019-03-27
StockPricePrediction-master\LICENSE, 1083 , 2019-03-27
StockPricePrediction-master\README.md, 2663 , 2019-03-27
StockPricePrediction-master\Report.pdf, 136581 , 2019-03-27
StockPricePrediction-master\input, 0 , 2019-03-27
StockPricePrediction-master\input\params.txt, 1502 , 2019-03-27
StockPricePrediction-master\input\symbols.txt, 8 , 2019-03-27
StockPricePrediction-master\requirements.txt, 162 , 2019-03-27
StockPricePrediction-master\screenshots, 0 , 2019-03-27
StockPricePrediction-master\screenshots\presentation.gif, 5455451 , 2019-03-27
StockPricePrediction-master\scripts, 0 , 2019-03-27
StockPricePrediction-master\scripts\Algorithms, 0 , 2019-03-27
StockPricePrediction-master\scripts\Algorithms\LSTN-RNN.py, 3947 , 2019-03-27
StockPricePrediction-master\scripts\Algorithms\Neural_Network.py, 16336 , 2019-03-27
StockPricePrediction-master\scripts\Algorithms\regression_helpers.py, 8744 , 2019-03-27
StockPricePrediction-master\scripts\Algorithms\regression_models.py, 2849 , 2019-03-27
StockPricePrediction-master\scripts\Algorithms\rnn_lstm.py, 4405 , 2019-03-27
StockPricePrediction-master\scripts\Algorithms\svm.py, 2580 , 2019-03-27
StockPricePrediction-master\scripts\Stock-Prediction-Copy1.ipynb, 878439 , 2019-03-27
StockPricePrediction-master\scripts\Stock-Prediction.ipynb, 1067999 , 2019-03-27
StockPricePrediction-master\scripts\add_s_and_p_index.py, 1404 , 2019-03-27
StockPricePrediction-master\scripts\feature_selection.py, 1669 , 2019-03-27
StockPricePrediction-master\scripts\fetch_stock_data.py, 2923 , 2019-03-27
StockPricePrediction-master\scripts\interpolation.py, 618 , 2019-03-27
StockPricePrediction-master\scripts\main.py, 749 , 2019-03-27
StockPricePrediction-master\scripts\normalization.py, 313 , 2019-03-27
StockPricePrediction-master\scripts\preprocessing.py, 2023 , 2019-03-27
StockPricePrediction-master\scripts\twitter-sentiment-analysis, 0 , 2019-03-27

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • ChineseSegmentUsingHashTable
    用python实现双字哈希字典,可用于中文分词(Using Python to realize double-character hash dictionary, which can be used for Chinese word segmentation)
    2019-04-20 23:09:29下载
    积分:1
  • mnist_CNN 深度学习小实例
    利用mnist数据集做深度学习小实例
    2018-05-03下载
    积分:1
  • Adaboost
    Python实现Adaboost算法,数据集为horseColic马疝气病数据集,准确率和sklearn库中的adaboost算法一样。(Python implementation adaboost algorithm, the data set is horseColic horse hernia disease data collection, accuracy and sklearn library adaboost the same algorithm.)
    2017-04-21 15:00:34下载
    积分:1
  • regress
    一个xgboost实现的回归模型预测,数据集来源于kaggle的taxi竞赛(Regression model prediction based on a xgboost implementation)
    2017-10-13 10:09:42下载
    积分:1
  • ID3算法的改进
    说明:  在Weka平台运行的ID3算法,对普通的ID3算法做了一点改进,有四个不同的改进,对应了四个不同的算法,适合实验报告和课程报告。直接可以运行,无需调试。(The ID3 algorithm running on the Weka platform has made a little improvement on the ordinary ID3 algorithm. There are four different improvements, corresponding to four different algorithms, which are suitable for experiment reports and course reports. It can run directly without debugging.)
    2019-11-25 21:00:55下载
    积分:1
  • python聊天机器人(扫码登陆网页版微信)
    python聊天机器人(扫码登陆网页版微信)
    2019-03-16下载
    积分:1
  • advantages
    关于粒子滤波的仿真程序,比较了粒子滤波和卡尔曼滤波的优缺点(On the simulation program of particle filter, the advantages and disadvantages of particle filter and Kalman filter are compared.)
    2018-11-14 16:19:23下载
    积分:1
  • boxcox
    说明:  boxcox函数的python实现,引用该函数可将偏态分布调整为正态分布(Python implementation of box Cox function)
    2020-06-17 09:40:01下载
    积分:1
  • sklearn-tree-BN-knn
    说明:  分类器的性能比较与调优: 使用scikit-learn 包中的tree,贝叶斯,knn,对数据进行模型训练,尽量了解其原理及运用。 使用不同分析三种分类器在实验中的性能比较,分析它们的特点。 本实验采用的数据集为house与segment。(Performance comparison and optimization of classifiers: We use tree, Bayesian and KNN in scikit-learnpackage to train the data model and try to understand its principle and application. The performances of three classifiers are compared and their characteristics are analyzed. The data set used in this experiment is house and segment.)
    2021-04-16 15:08:53下载
    积分:1
  • 《Python分析与应用:从获取到可视化》源代码
    【实例简介】
    2021-05-18 10:33:57下载
    积分:1
  • 696516资源总数
  • 106914会员总数
  • 0今日下载