A Comparative Study of Different Machine Learning Algorithms in Predicting the Content of Ilmenite in Titanium Placer
In this study, the ilmenite content in beach placer sand was estimated using seven soft computing techniques, namely random forest (RF), artificial neural network (ANN), <i>k</i>-nearest neighbors (kNN), cubist, support vector machine (SVM), stochastic gradient boosting (SGB), and classi...
Main Authors: | , , , , , , , |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-01-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/10/2/635 |