Super easy Python Stock price forecasting (using ensemble voting) Machine learning

1. tool installation

$ pip install scikit-learn pandas_datareader rgf-python xgboost

2. file creation

3. execution

$ python

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




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

Recommended from Medium

Straightforward Time Series DBs with Redis 5.X — part 1 :: RedisTimeSeries module

Config Driven Reactive Programming in Ruby

Gaspar Nagy on How to Improve Development and Business with BDD Testing

ServerAndGo 2.0 Beta released today!

“Hello Many Worlds” in Quantum Computer

Difference between em and rem - CSS

AWS PowerTools Layer — How to setup in SAM

Pygame Fast Food Menu Skeleton. Am I Over Thining It? (***)

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


More from Medium

Artificial Neural Network in Python; ASD Detection in Fetuses Using an Ultrasound Measurement

What is Agglomerative clustering and how to use it with Python Scikit-learn

Functions that I wish existed in Python/Tensorflow/Sci-kit

Paradigms of various LSTM Networks