RSML Research Group at University of Idaho

Plant-Based Recovery of Rare Earth Elements: Assessing the Feasibility of Phytomining in Idaho

Bagging Regressor

MLP Classifier

Logistic Regression Classifier

Gradient Boosting Classifier

Random Forest Classifier

Histog Graddient Boosting Classifier

K-Nearest Neighbors Classifier

CyCon Perceptron

CyCon NC Classifier

CyCon Dummy Classifier

ML Case Study #5

ML Case Study #4

ML Case Study #3

Ridge Regression

Decision Tree Classifier

Adaptive Boosting (AdaBoost) Regression

ML Phytoremediation Case Study #2

ML Phytomining Case Study #1

Multiclass, multivariable classification using AdaBoost classifier

Multiclass, multivariable classification using bagging classifier

Multiclass, multivariable classification using ridge classifier

Support Vector Regression (SVR): Phytomining

KNN Regression

Decision Tree Regression

Multivariable Regression using Gaussian Process Regression

Multivariable Regression using LinearSVR

Multivariable Regression using KNeighborsRegressor

Energy Consumption using AdaboostRegressor

Multivariable Regression using ExtraTreesRegressor