Skip to content

Latest commit

 

History

History
16 lines (11 loc) · 1016 Bytes

File metadata and controls

16 lines (11 loc) · 1016 Bytes

Contributors

Ariel Guerrero
Joshua Cherry
Hunter Long

Description

Analyzed data to find correlations between Pokémon types, stats, attributes, etc and displayed descriptive summary statistics. Utilized sklearns linear regression to train a machine learning model to predict the stats, types and physical attributes of future Pokémon.

Setup

  • import sklearn, numpy, pandas, and matplotlib (pip install these packages if the script fails to run)

  • analysis/analysis.py

    • Main driver of the program, run this file to start up the project