Mongabay News

Scientists can’t agree on where the world’s forests are

A deceptively simple question underlies many global environmental policies: where, exactly, are the world’s forests? A new study suggests the answer depends heavily on which map one consults—and that ...

Fentanyl or phony? Machine learning algorithm learns to pick out opioid signatures

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...
IEEE

Enhancing Sleep Stage Classification With Single Channel EEG: Feature Extraction and Random Forest-XGBoost Model

Abstract: Sleep stage classification, essential for diagnosing sleep disorders, monitoring neurological health, and advancing cognitive neuroscience. Traditionally involves manual scoring of ...
Frontiers

Comparative evaluation of fast-learning classification algorithms for urban forest tree species identification using EO-1 hyperion hyperspectral imagery

Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...
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 ...
Scientific Research Publishing

Raczko, E. and Zagajewski, B. (2017) Comparison of Support Vector Machine, Random Forest and Neural Network Classifiers for Tree Species Classification on Airborne ...

ABSTRACT: Making the distinction between different plantation tree species is crucial for creating reliable and trustworthy information, which is critical in forestry administration and upkeep. Over ...
IEEE

An Intelligent Classification Method for Vibration Signals Based on Random Forest

Abstract: Due to the complexity of fiber optic vibration signals, using traditional classification methods to classify signals is inaccurate. Effective fiber optic sensor data classification has ...
The New York Times

Paris Paralympics 2024: How the classification system works

PR1, W1, T51, F58, SL4, KL3, SM11. This is not a test to crack a code. But you will see a series of letter and number combinations while engaging with the Paralympics in Paris. At the Olympics, there ...
GitHub

Random forest classification generates a single outcome by combining the output of several decision trees. Its popularity has been spurred by its versatility and ease of use ...

Use an example to understand how random forests operate. Recognize the effects of various hyperparameters. Apply them to a scikit-learn classification issue. Leo Breiman and Adele Cutler created the ...