Skip to content

malithjayasinghe/ML_PredictiveModels

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

2 Commits
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Using Machine Learning for Performance Predictions

This project implements the following Machine Learning models,

  • Support Vector Regression - Kernels: Linear, RBF, Polynomial
  • Random Forest Regression
  • XGBoost
  • Bayesian Gaussian Process

Package Installations

The following packages must be installed in order to run this program,

  • numpy - 1.15.4v
  • scipy - 1.2.0v
  • pandas - 0.23.4v
  • scikit-learn - 0.20.1v
  • xgboost - 0.81v
  • pymc3 - 3.5v
  • Matplotlib -
  • seaborn - 0.9.0v

Running

  1. Specify the file_path of the dataset you want to run
  2. Specify the dependent variable desired - Average latency/Throughput

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 95.1%
  • C++ 3.1%
  • C 1.1%
  • Cuda 0.4%
  • Java 0.1%
  • TeX 0.1%
  • Other 0.1%