Results 1 to 10 of about 1,605 (153)
ADASYN-LOF Algorithm for Imbalanced Tornado Samples
Atmosphere, 2022 Early warning and forecasting of tornadoes began to combine artificial intelligence (AI) and machine learning (ML) algorithms to improve identification efficiency in the past few years.
Zhipeng Qing +5 more
doaj +2 more sources
2018 4th International Conference on Science and Technology (ICST), 2018 Annually about 1,500 cases of cervical cancer are found in Indonesia, which made Indonesia as the country with the highest number of cervical cancer cases in the world. Cervical cancer screening and HPV testing are done with a Pap smear test. However, this examination requires a lot of time, costly and highly susceptible bias of the observer during the
Yulia Ery Kurniawati +2 more
exaly +4 more sources
ENSEMBLE CNN WITH ADASYN FOR MULTICLASS CLASSIFICATION ON CABBAGE PESTS
BarekengImage classification is a complex process influenced by various factors, one of which is the amount of image data. In the context of cabbage pest classification, data often exhibits a significant class imbalance, where certain pests are more prevalent ...
Nabila Ayunda Sovia +1 more
doaj +2 more sources
Application of ADASYN and Optuna in the XGBoost Algorithm for Stunting Detection
Journal of Applied Informatics and ComputingThis study aims to develop an early detection model for childhood stunting risk using a machine learning approach based on Extreme Gradient Boosting (XGBoost), integrated with the Adaptive Synthetic Sampling (ADASYN) technique for data balancing and ...
Fastabyq Putra Sadewa, Defri Kurniawan
doaj +2 more sources
Data Augmentation and Machine Learning algorithms for multi-class imbalanced morphometrics data of stingless bees [PDF]
HeliyonThe study focusses on handling of multiclass imbalanced data on classification of stingless bee samples by employing data balancing techniques, namely Synthetic Minority Oversampling Technique (SMOTE) and Adaptive Synthetic (ADASYN) approach.
Daisy Salifu +4 more
doaj +2 more sources
The Effect of the ADASYN Method on Widespread Metrics of Machine Learning Efficiency
Современные информационные технологии и IT-образование, 2019 The article presents the results of experimental work comparing the performance metrics of machine learning algorithms on imbalanced text corpora using the method of synthetic data generation ADASYN and without it.
Mukhit A. Baimakhanbetov +4 more
doaj +2 more sources
Credit Risk Prediction Based on Improved ADASYN Sampling and Optimized LightGBM
Journal of Social ComputingA credit risk prediction model named KM-ADASYN-TL-FLLightGBM (KADT-FLightGBM) is proposed in this study. Firstly, to overcome the limitation of traditional sampling methods in dealing with imbalanced datasets, an improved ADASYN sampling with K-means ...
Mei Song, He Ma, Yi Zhu, Mengdi Zhang
doaj +2 more sources
Predicting Employee Turnover Based on Improved ADASYN and GS-CatBoost
MathematicsIn corporate management practices, human resources are among the most active and critical elements, and frequent employee turnover can impose substantial losses on firms.
Shuigen Hu, Kai Dong
doaj +2 more sources
APPLICATION OF ADASYN OVERSAMPLING TECHNIQUE ON K-NEAREST NEIGHBOR ALGORITHM
BarekengThe K-Nearest Neighbor Algorithm is a commonly used data mining algorithm for classification due to its effectiveness with large datasets and noise.
Herina Marlisa +3 more
doaj +2 more sources
ADASYN−Random Forest Based Intrusion Detection Model [PDF]
2021 4th International Conference on Signal Processing and Machine Learning, 2021 Intrusion detection has been a key topic in the field of cyber security, and the common network threats nowadays have the characteristics of varieties and variation. Considering the serious imbalance of intrusion detection datasets will result in low classification performance on attack behaviors of small sample size and difficulty to detect network ...
Zhewei Chen, Linyue Zhou, Wenwen Yu
openaire +2 more sources