Frontiers

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

1 Sibley School of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY, United States 2 Department of Animal Sciences, Cornell University, Ithaca, NY, United States The lack of ...
IEEE

Android Malware Detection Using API Calls and Permissions with Random Forest Classifier

Abstract: Android malware poses a persistent and evolving threat to mobile security, considering its capability to compromise sensitive user data and evade traditional detection methods. While ...
Game Rant

How to Revive in 99 Nights in the Forest

Somiya Adrees is a writer at GameRant. Her gaming journey began at a young age with classics like Super Mario Bros., Sonic the Hedgehog, and Disney's Aladdin in Nasira's Revenge (all of which she ...
IEEE

Facilitating Seamless Communication through Voice-Enhanced Sign Language and Gesture Recognition with Random Forest Classifier and Graph Convolution Networks

Abstract: An innovative system designed to enhance communication for individuals using sign language. Developed in Python, the system leverages a Random Forest classifier to accurately interpret hand ...
Frontiers

A hybrid fuzzy logic–Random Forest model to predict psychiatric treatment order outcomes: an interpretable tool for legal decision support

Background: Decisions surrounding involuntary psychiatric treatment orders often involve complex clinical, legal, and ethical considerations, especially when patients lack decisional capacity and ...
GitHub

krish-thakker/nba-mvp-predictor

Fetch and preprocess NBA player and team statistics for regular seasons. Label seasons with actual MVP winners. Train a Random Forest classifier to predict NBA MVPs based on per-game and team ...
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 ...
C&EN

Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML

The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate.
Scientific Research Publishing

Remote Sensing Prospecting Method Based on Random Forest in Eastern Botswana Mining Area ()

In this study, multi-source remote sensing data and machine learning algorithms were used to delineate the prospect area of remote sensing geological prospecting in eastern Botswana. Landsat 8 remote ...