首页|New Machine Learning Data Have Been Reported by Researchers at University of the Witwatersrand (Comparison of Individual and Ensemble Machine Learning Models fo r Prediction of Sulphate Levels In Untreated and Treated Acid Mine Drainage)
New Machine Learning Data Have Been Reported by Researchers at University of the Witwatersrand (Comparison of Individual and Ensemble Machine Learning Models fo r Prediction of Sulphate Levels In Untreated and Treated Acid Mine Drainage)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – Data detailed on Machine Learning have been presented. According to news reportingoriginating in Johannesburg, South Africa, by NewsRx journalists, research stated, “Machine learning wasused to pr ovide data for further evaluation of potential extraction of octathiocane (S8), a commerciallyuseful by-product, from Acid Mine Drainage (AMD) by predicting su lphate levels in an AMD water qualitydataset. Individual ML regressor models, n amely: Linear Regression (LR), Least Absolute Shrinkage andSelection Operator ( LASSO), Ridge (RD), Elastic Net (EN), K-Nearest Neighbours (KNN), Support VectorRegression (SVR), Decision Tree (DT), Extreme Gradient Boosting (XGBoost), Rand om Forest (RF),Multi-Layer Perceptron Artificial Neural Network (MLP) and Stack ing Ensemble (SE-ML) combinationsof these models were successfully used to pred ict sulphate levels.”
JohannesburgSouth AfricaAfricaCybo rgsEmerging TechnologiesMachine LearningUniversity of the Witwatersrand
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