Seismic landslide susceptibility assessment based on ADASYN-LDA model
IOP Conference Series: Earth and Environmental Science, 2020 AbstractSeismic landslide susceptibility (SLS) assessment can be used to estimate the susceptibility of landslides induced by an earthquake, which has great significance for emergency measure making and land use planning to mitigate the landslide hazard and risk.
Shuhao Zhang, Peiqiao Yu
openaire +1 more source
Klasifikasi Balita Terkait Kasus Stunting Di Kota Surabaya Menggunakan Classification And Regression Trees (CART) dengan Adaptive Synthetic Nominal (ADASYN-N) dan Adaptive Synthetic K-Nearest Neighbor (ADASYN-kNN) [PDF]
, 2020 Stunting merupakan masalah gizi kronis yang disebabkan oleh defisiensi nutrien selama seribu hari pertama kehidupan yang menyebabkan penurunan kemampuan kognitif dan motorik serta penurunan performa kinerja fisik. Jumlah balita stunting di Indonesia kini
Insyroh, Winantri Nurbuwah
core
Rhyming in the cold: first evidence of soniferous fishes in the Southern Ocean
Remote Sensing in Ecology and Conservation, EarlyView.The acoustic ecology of Southern Ocean fishes remains unknown due to a lack of dedicated acoustic research on the fishes of this ocean. Passive acoustic monitoring data were collected at the South African sub‐Antarctic Prince Edward Islands using an underwater acoustic recorder, and towed underwater Ski‐Monkey cameras were deployed to identify fish ...
Fannie W. Shabangu +5 more
wiley +1 more source
Improving imbalanced class intrusion detection in IoT with ensemble learning and ADASYN-MLP approach [PDF]
The exponential growth of the internet of things (IoT) has revolutionized daily activities, but it also brings forth significant vulnerabilities. intrusion detection systems (IDS) are pivotal in efficiently detecting and identifying suspicious activities
Al Amien, Januar +3 more
core +2 more sources
Results with different balancing methods (no balancing, random majority subsampling and ADASYN oversampling) and calibration methods (no calibration, Beta Calibration and Isotonic Calibration). [PDF]
, 2022 Results with different balancing methods (no balancing, random majority subsampling and ADASYN oversampling) and calibration methods (no calibration, Beta Calibration and Isotonic Calibration).
Juan-Carlos Perez-Cortes (13104463) +6 more
core +1 more source
IJAIN (International Journal of Advances in Intelligent Informatics)Stroke is a serious medical condition resulting from disturbances in blood flow to the brain, signaling a chronic health issue that requires an immediate response.
Adiwijaya Adiwijaya +1 more
doaj +1 more source
Expert Systems, Volume 43, Issue 8, August 2026.ABSTRACT Improving classification performance on imbalanced datasets remains a challenging problem in machine learning. Synthetic oversampling techniques such as SMOTE are widely used to address class imbalance; however, their random interpolation strategy often ignores structural data properties, which may affect classifier generalisation.
Jose L. Morillo‐Salas +3 more
wiley +1 more source
ENSEMBLE RESAMPLING SUPPORT VECTOR MACHINE, MULTINOMIAL REGRESSION TO MULTICLASS IMBALANCED DATA
BarekengImbalanced data is a commonly encountered issue in classification analysis. This issue gives rise to prediction errors in the classification process, which in turn affects the sensitivity, particularly in the minority class.
Laila Qadrini +6 more
doaj +1 more source
Annals of Neurology, Volume 100, Issue 1, Page 36-47, July 2026.Objective The objective of this study was to examine whether machine learning has the capacity to prospectively identify and predict the emergence of Fragile X‐associated tremor/ataxia syndrome (FXTAS) among male fragile X premutation carriers (PCs). Methods We explored neuropsychological and motor evaluation metrics, brain magnetic resonance imaging ...
Chitrabhanu Gupta +10 more
wiley +1 more source
Optimasi Metode CART Menggunakan Metode Bagging Pada Studi Kasus Data Imbalance Berbasis Metode Adasyn [PDF]
Penelitian ini membahas mengenai permasalahan data imbalance yang menyebabkan kinerja dari model klasifikasi menjadi tidak optimal. Dalam penelitian ini menerapkan metode Adaptive Synthetic Sampling (ADASYN) untuk menangani permasalahan data imbalance ...
Khana Pujiyanti
core +2 more sources