Chromatography Online

Optimizing HSSE-GC-MS and Machine Learning for Forensic Gender Classification from Human Scent

Researchers have optimized a headspace sorptive extraction (HSSE) method coupled with gas chromatography-mass spectrometry ...
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 ...
Frontiers

Artificial intelligence-based diagnostic model for schizophrenia in individuals living with HIV

Schizophrenia is one of the most prevalent severe mental disorders among people living with HIV (PLWH). Delayed diagnosis and misdiagnosis contribute to poor prognosis and substantial economic burden ...
Frontiers

Advancing standardized cattle behavior classification with a random forest model evaluated across diverse datasets

The lack of precise, autonomous tools for monitoring and classifying cattle behavior limits farmers’ ability to make proactive and informed decisions regarding grazing and herd management. Currently, ...
IEEE

Typhoon Classification and Path Prediction Based on XGBoost and Random Forest Modeling

Abstract: The aim of this paper is to construct a typhoon classification and path prediction system based on XGBoost and random forest model to improve the accuracy of typhoon prediction and disaster ...
IEEE

Maximum Depth Parameter Explorations of Random Forest Method For Breast Cancer Classification On RNA Mutations Data

One kind of cancer that affects women globally is breast cancer. Machine learning techniques are a possible alternative approach to increase the precision of breast cancer detection. One popular ...
Scientific Research Publishing

Kirasich, K., Smith, T. and Sadler, B. (2018) Random Forest vs Logistic Regression: Binary Classification for Heterogeneous Datasets. SMU Data Science Review, 1, Article 9.

ABSTRACT: The Efficient Market Hypothesis postulates that stock prices are unpredictable and complex, so they are challenging to forecast. However, this study demonstrates that it is possible to ...