A comprehensive survey on rare event prediction
Rare event prediction involves identifying and forecasting events with a low probability using
machine learning (ML) and data analysis. Due to the imbalanced data distributions, where …
machine learning (ML) and data analysis. Due to the imbalanced data distributions, where …
A Comprehensive Survey on Rare Event Prediction
CS Jayakody Kankanamalage… - ACM Computing …, 2024 - scholarcommons.sc.edu
Rare event prediction involves identifying and forecasting events with a low probability using
machine learning (ML) and data analysis. Due to the imbalanced data distributions, where …
machine learning (ML) and data analysis. Due to the imbalanced data distributions, where …
Weighted logistic regression for large-scale imbalanced and rare events data
M Maalouf, M Siddiqi - Knowledge-Based Systems, 2014 - Elsevier
Latest developments in computing and technology, along with the availability of large
amounts of raw data, have led to the development of many computational techniques and …
amounts of raw data, have led to the development of many computational techniques and …
Penerapan Metode Machine Learning dalam Klasifikasi Risiko Kejadian Berat Badan Lahir Rendah di Indonesia
Penelitian ini akan mengkaji penerapan beberapa metode machine learning dengan
memperhatikan kasus imbalanced data dalam pemodelan klasifikasi untuk penentuan risiko …
memperhatikan kasus imbalanced data dalam pemodelan klasifikasi untuk penentuan risiko …
Leading indicators and maritime safety: predicting future risk with a machine learning approach
L Kretschmann - Journal of Ship** and Trade, 2020 - Springer
The ship** industry has been quite successful in reducing the number of major accidents
in the past. In order to continue this development in the future, innovative leading risk …
in the past. In order to continue this development in the future, innovative leading risk …
Logistic regression in large rare events and imbalanced data: A performance comparison of prior correction and weighting methods
The purpose of this study is to use the truncated Newton method in prior correction logistic
regression (LR). A regularization term is added to prior correction LR to improve its …
regression (LR). A regularization term is added to prior correction LR to improve its …
Comparison of Machine Learning Methods in Classifying Poverty in Indonesia in 2018
Poverty is still one of the main problems in economic development besides inequality,
unemployment, and economic growth. This study aims to model poverty directly using a …
unemployment, and economic growth. This study aims to model poverty directly using a …
A study on survival analysis methods using neural network to prevent cancers
CY Bae, BS Kim, SH Jee, JH Lee, ND Nguyen - Cancers, 2023 - mdpi.com
Simple Summary According to cancer statistics published in 2020, there were 19.3 million
new cancer cases and almost 10.0 million cancer deaths worldwide. This suggests that …
new cancer cases and almost 10.0 million cancer deaths worldwide. This suggests that …
On the prediction of rare events when sampling from large data
J de Haan-Ward, S J. Bonner… - … in Statistics-Simulation …, 2024 - Taylor & Francis
When modeling rare events using logistic regression, independent samples of event
occurrence (ones) and nonoccurrence (zeros) are commonly taken from large datasets in …
occurrence (ones) and nonoccurrence (zeros) are commonly taken from large datasets in …
[HTML][HTML] Predicting Air Traffic Flow Management hotspots due to weather using Convolutional Neural Networks
I Martínez, J García-Heras, A Jardines… - … Applications of Artificial …, 2024 - Elsevier
Convective weather is a major source of disruption to air traffic operations responsible for
roughly one third of en-route delay in the network. Understanding how weather impact air …
roughly one third of en-route delay in the network. Understanding how weather impact air …