Machine learning technology in biodiesel research: A review

M Aghbashlo, W Peng, M Tabatabaei… - Progress in Energy and …, 2021‏ - Elsevier
Biodiesel has the potential to significantly contribute to making transportation fuels more
sustainable. Due to the complexity and nonlinearity of processes for biodiesel production …

A random forest guided tour

G Biau, E Scornet - Test, 2016‏ - Springer
The random forest algorithm, proposed by L. Breiman in 2001, has been extremely
successful as a general-purpose classification and regression method. The approach, which …

Generalized random forests

S Athey, J Tibshirani, S Wager - 2019‏ - projecteuclid.org
Generalized random forests Page 1 The Annals of Statistics 2019, Vol. 47, No. 2, 1148–1178
https://doi.org/10.1214/18-AOS1709 © Institute of Mathematical Statistics, 2019 GENERALIZED …

Estimation and inference of heterogeneous treatment effects using random forests

S Wager, S Athey - Journal of the American Statistical Association, 2018‏ - Taylor & Francis
Many scientific and engineering challenges—ranging from personalized medicine to
customized marketing recommendations—require an understanding of treatment effect …

Machine unlearning for random forests

J Brophy, D Lowd - International Conference on Machine …, 2021‏ - proceedings.mlr.press
Responding to user data deletion requests, removing noisy examples, or deleting corrupted
training data are just a few reasons for wanting to delete instances from a machine learning …

Application of machine learning in disease prediction

PS Kohli, S Arora - 2018 4th International conference on …, 2018‏ - ieeexplore.ieee.org
The application of machine learning in the field of medical diagnosis is increasing gradually.
This can be contributed primarily to the improvement in the classification and recognition …

Predicting compressive strength of geopolymer concrete using machine learning

P Gupta, N Gupta, KK Saxena - Innovation and Emerging …, 2023‏ - World Scientific
The anaconda software required python code in order to run the utilized individual K-nearest
neighbor (KNN), random forest regression (RFR), and linear regression (LR) models. The …

A soft voting ensemble classifier for early prediction and diagnosis of occurrences of major adverse cardiovascular events for STEMI and NSTEMI during 2-year follow …

SWA Sherazi, JW Bae, JY Lee - PloS one, 2021‏ - journals.plos.org
Objective Some researchers have studied about early prediction and diagnosis of major
adverse cardiovascular events (MACE), but their accuracies were not high. Therefore, this …