Published June 28, 2024 | Version v1
Software Open

Machine learning models for predicting Estonian phosphorite dissolution in hydrochloric acid

  • 1. Department of Chemistry and Biotechnology
  • 2. Department of Materials and Environmental Technology

Description

This collection contains ML model trained to predict phosphorite concentration in hydrochloric acid and a Python notebook modelling.ipynb that creates models and gives an example of how to upload and use them.

Abbreviation: 

Linear regression - lr 

Linear polynomial regression of second order - lpr2  

Support vector regression  - svr  

Support vector regression with polynomial features - svr_pl2  

Random forest regression - rf  

Random forest regression with polynomial features - rf_pl2  

CatBoost regression - catr  

CatBoost regression with polynomial features - catr_pl2  

Neural net - NN 

Files

modeling.ipynb

Files (1.3 MB)

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