Skip to content

ssomagani/FlightPredictionML

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

FlightPredictionML

Example of ML model implementation in VoltDB to predict delays in flights. The library H2O is used to build the model since it's a market leader in machine learning and also provides the convenience of exporting models as Java code

Steps to run (assuming you have VoltDB and H2O installed)

  1. Create a new flow or load a flow from h2o/ to start off a previously built model.
  2. Train the model using your own data or data from data/ (using the H2O Flow UI or a language SDK)
  3. Export the trained model as Java class.
  4. Create a new stored procedure that accepts new events and calls the trained model class to make the predictions

In this project, I have implemented a Linear Regression Model for Flight Prediction. On the test set, this model only gets about 69% accuracy but it's a place to start.

About

Implementation of H2O Model in VoltDB

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages