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 …
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
As global climate change intensifies, climate protection is important for the sustainable
development of human society. In the process of urbanization and industrialization, carbon …
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 …
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 …
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
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 …
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 …
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
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 …
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
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 …
important to model and monitor urban growth in mega cities. Although several researchers …