Opinion

Can we trust algorithms with our money?

Contemporary research suggests that AI improves efficiency in areas such as fraud detection and portfolio optimisation due to its vast data and analytical prowess. However, it also bears the risks of ...
Frontiers

Numerical foundations for scalable statistical and machine learning methods

Across modern data-intensive disciplines, the union of numerical computation, statistics, and machine learning has become ...
IEEE

Enhancing Prostate Cancer Classification by Leveraging Key Radiomics Features and Using the Fine-Tuned Linear SVM Algorithm

Abstract: This paper focuses on enhancing machine learning (ML)-based diagnosis and clinical decision-making by leveraging radiomics data, which provides a quantitative description of grayscale ...
holisticai

Bias Mitigation Strategies and Techniques for Classification Tasks

The bias problem in classification tasks and the different strategies used for bias mitigation. How these strategies are grouped into categories and a brief introduction of the most representative ...
IEEE

Separation and Classification of Concurrent Partial Discharge Signals Using Statistical-Based Feature Analysis

Abstract: In this paper, an algorithm for feature extraction and classification of high-pressure gas insulation system defects based on statistical analysis of time-domain parameters of partial ...
Investopedia

Predictive Modeling: Techniques, Uses, and Key Takeaways

Investopedia contributors come from a range of backgrounds, and over 25 years there have been thousands of expert writers and editors who have contributed. Jared Ecker is a researcher and fact-checker ...
Visual Studio Magazine

Binary Classification Using LightGBM

Dr. James McCaffrey from Microsoft Research presents a full-code, step-by-step tutorial on using the LightGBM tree-based system to perform binary classification (predicting a discrete variable that ...
InfoWorld

The engines of AI: Machine learning algorithms explained

Machine learning and deep learning have been widely embraced, and even more widely misunderstood. In this article, I’ll step back and explain both machine learning and deep learning in basic terms, ...
InfoWorld

14 popular AI algorithms and their uses

Large language models have captured the news cycle, but there are many other kinds of machine learning and deep learning with many different use cases. Amid all the hype and hysteria about ChatGPT, ...
Scientific Research Publishing

A Novel Efficient and Effective Preprocessing Algorithm for Text Classification ()

1 College of Information Science and Technology, Jinan University, Guangzhou, China. 2 University of Birmingham Joint Institute, Jinan University, Guangzhou, China. Text classification is an essential ...
Nature

Earthquake multi-classification detection based velocity and displacement data filtering using machine learning algorithms

Earthquake is one of the natural disasters that have a big impact on society. Currently, there are many studies on earthquake detection. However, the vibrations that were detected by sensors were not ...
Frontiers

An efficient approach for textual data classification using deep learning

Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories ...