This paper takes education data mining as the research theme, mine the existing massive
education big data, compares the analysis methods of existing data models, and proposes …

We propose a method for selecting the optimal set of weather features for wind energy
prediction. This problem is tackled by developing a wrapper approach that employs binary …

Monitoring students' academic progress is vital for ensuring timely completion of their
studies and supporting at-risk students. Educational Data Mining (EDM) utilizes machine …

PerformanceX is a proposed system that combines Educational Data Mining (EDM)
techniques to enhance student performance and reduce dropout rates. It employs a hybrid …

In higher education institutions (HEI), the ability to predict student grades as an early
warning system is one of the important areas that gained attention to improve educational …

Objectives Women's attendance to cervical cancer screening (CCS) is a major concern for
healthcare providers in community. This study aims to use the various algorithms that can …

The high dropout rate and the low percentage of undergraduate students who graduate on
time are some of the problems at higher education institutions. Various research has been …

Assessments and critical feedback play a crucial role in helping students not only master a
skill but also apply it effectively. Educational data mining (EDM) and machine learning (ML) …

Introduction: This article is a product of the research “Ensemble methods to estimate the
academic performance of higher education students”, developed at the Universidad Distrital …

By improving the logistic regression function and selecting a step‐by‐step fitting result using
the least square method as the input of the logistic regression model, this paper analyzes …