Data balancing techniques for predicting student dropout using machine learning

N Mduma - Data, 2023 - mdpi.com
Predicting student dropout is a challenging problem in the education sector. This is due to
an imbalance in student dropout data, mainly because the number of registered students is …

[HTML][HTML] Urban land use simulation and carbon-related driving factors analysis based on RF-CA in Shanghai, China

L Ye, S Zhao, H Yang, X Chuai, L Zhai - Ecological Indicators, 2024 - Elsevier
As global climate change intensifies, climate protection is important for the sustainable
development of human society. In the process of urbanization and industrialization, carbon …

Generation of radiometric, phenological normalized image based on random forest regression for change detection

DK Seo, YH Kim, YD Eo, WY Park, HC Park - Remote Sensing, 2017 - mdpi.com
Efforts have been made to detect both naturally occurring and anthropogenic changes to the
Earth's surface by using satellite remote sensing imagery. There is a need to maintain the …

What drives urban growth in Pune? A logistic regression and relative importance analysis perspective

LN Kantakumar, S Kumar, K Schneider - Sustainable Cities and Society, 2020 - Elsevier
Proactive planning and management of rapidly urbanizing cities using up-to-date spatially
explicit datasets is an urgent need. This requires a good understanding of the driving factors …

Mapping hourly population dynamics using remotely sensed and geospatial data: a case study in Beijing, China

X Zhao, Y Zhou, W Chen, X Li, X Li… - GIScience & Remote …, 2021 - Taylor & Francis
High spatiotemporal population data are critical for a wide range of applications (eg urban
planning and management, risk assessment, and epidemic control). However, such data are …

[PDF][PDF] Data Balancing Techniques for Predicting Student Dropout Using Machine Learning. Data 2023, 8, 49

N Mduma - 2023 - africa.ai4d.ai
Predicting student dropout is a challenging problem in the education sector. This is due to
an imbalance in student dropout data, mainly because the number of registered students is …

A comparative study of machine learning techniques to simulate land use changes

M Ahmadlou, MR Delavar, A Basiri, M Karimi - Journal of the Indian …, 2019 - Springer
Abstract Design and development of a practical land use change (LUC) model require both
a high prediction accuracy, to predict the future changes, and a well-fitted model reflecting …

Rule based end-to-end learning framework for urban growth prediction

S Pal, SK Ghosh - arXiv preprint arXiv:1711.10801, 2017 - arxiv.org
Due to the rapid growth of urban areas in the past decades, it has become increasingly
important to model and monitor urban growth in mega cities. Although several researchers …