Super easy Python stock price forecast (using keras / gru) Deep learning

1. tool installation

$ pip install scikit-learn keras pandas_datareader

2. file creation

3. execution

$ python pred.py

That’s super easy!

4. result

As a result of calculation with the same data and features, MLP are the best among XGBoost, DNN, LSTM, GRU, RNN, LogisticRegression, k-nearest neighbor, RandomForest, BernoulliNB, SVM, RGF, MLP, Bagging, Voting, Stacking.

XGBoost            0.5119047619047619
DNN 0.5496031746031746
LSTM 0.5178571428571429
GRU 0.5138888888888888
RNN 0.5376984126984127
LogisticRegression 0.5496031746031746
k-nearest neighbor 0.5198412698412699
RandomForest 0.49603174603174605
BernoulliNB 0.5496031746031746
SVM 0.5396825396825397
RGF 0.5158730158730159
MLP 0.5694444444444444
Bagging 0.5297619047619048
Voting 0.5416666666666666
Stacking 0.5218253968253969

5. reference

--

--

--

https://github.com/10mohi6

Love podcasts or audiobooks? Learn on the go with our new app.

Recommended from Medium

Clarifying Transparency Within And Outside Your Software Organization

Towards building an eBPF Based Network Data Plane

Database for Digital Marketers — 1.1 (Select, Count & Where Clause)

Building Laravel Apps in an 80/20 fashion

How to join multiple KStreams in Redpanda

Send AMP Emails with Ruby on Rails

Getting Started with Elasticsearch Development in Node.js

Common Way of Managing Dependencies of an iOS App

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store
10mohi6

10mohi6

https://github.com/10mohi6

More from Medium

Support Vector Machine with Kernels and Python Iterators

Generate art using aggdraw and Python — Part 1

Stock Market Scikit-learn Tutorial: Coding

Regular Expression (Regex) for Common Situations