Scientific Research Publishing

Proposal for a Machine Learning Model to Improve Hauling Productivity in an Open-Pit Mine ()

This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...
Analytics Insight

10 Must-Know Machine Learning Algorithms for Data Science in 2026

Machine learning algorithms help computers analyse large datasets and make accurate predictions automatically.Classic models ...
Devdiscourse

AI in critical care: Predictive algorithms can support sepsis decision-making

A new study explores how artificial intelligence models can support clinical decision-making for sepsis management. Their research, titled “Responsible AI for Sepsis Prediction: Bridging the Gap ...
BMJ

Estimating prevalence and predictors of glucose-lowering overtreatment among older adults with type 2 diabetes in long-term care and community settings: a machine learning ...

Objective To estimate the prevalence of potential overtreatment of type 2 diabetes mellitus (T2DM) among older adults and to develop and compare predictive models to identify patient and physician ...
Devdiscourse

Stacked AI model improves credit default forecasting

A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine ...
Visual Studio Magazine

Decision Tree Regression from Scratch Without Pointers or Recursion Using C#

A decision tree regression system incorporates a set of if-then rules to predict a single numeric value. Decision tree regression is rarely used by itself because it overfits the training data, and so ...
IEEE

The Application of Random Forest Regression Algorithm for Price Prediction on Used Vehicle Prices in Malaysia

Abstract: The Malaysian used vehicle market faces ongoing challenges in price transparency, leading to inconsistencies in buyer-seller expectations and decision-making. This study proposes AutoPrice, ...
IEEE

Phishing Attack Detection using Logistic Regression and Novel Random Forest Algorithm to improve Accuracy

Abstract: —The objective is to more accurately forecast phishing attacks that harvest sensitive data from unsuspecting users by utilizing Logistic Regression in comparison to the Novel Random Forest ...
Scientific Research Publishing

Widiyasono, A., Fakhrulddin, M. and Kusuma, Y. (2021) IoT Device Malware Detection Using Random Forest Algorithm. Proc. Int. Conf. Inf. Technol. Syst., 2021, 234-240.

ABSTRACT: This study presents a comparative analysis of machine learning models for threat detection in Internet of Things (IoT) devices using the CICIoT2023 dataset. We evaluate Logistic Regression, ...