A Material Type Prediction Model Based on Machine Learning Technology
DOI:
https://doi.org/10.53469/jrse.2024.06(11).14Keywords:
Supervised Learning, Classification Problems, Feature Engineering, Scaling, Python, Material TypeAbstract
In materials science, traditional experimental and computational approaches require the investment of enormous amounts of time and resources, and the experimental conditions limit the use of these methods. Sometimes, traditional approaches may not yield satisfactory results for the desired purpose. Therefore, it is essential to develop a new approach to accelerate experimental progress and avoid unnecessary waste of time and resources.
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Copyright (c) 2024 Seetaram Nagaraju Naik
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
