Results 11 to 20 of about 2,573 (145)
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
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APPLICATION OF ADASYN OVERSAMPLING TECHNIQUE ON K-NEAREST NEIGHBOR ALGORITHM [PDF]
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
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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
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Credit Risk Prediction Based on Improved ADASYN Sampling and Optimized LightGBM [PDF]
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
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ENSEMBLE CNN WITH ADASYN FOR MULTICLASS CLASSIFICATION ON CABBAGE PESTS [PDF]
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
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Data Balancing Techniques Using the PCA-KMeans and ADASYN for Possible Stroke Disease Cases [PDF]
JOIN: Jurnal Online InformatikaImbalanced data happens when the distribution of classes is not equal between positive and negative classes. In healthcare, the majority class typically consists of healthy patient data, while the minority class contains sick patient data. This condition
Uung Ungkawa, Muhammad Avilla Rafi
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Deteksi Transaksi Fraud Kartu Kredit Menggunankan Oversampling ADASYN dan Seleksi Fitur SVM-RFECV [PDF]
Jurnal Teknologi Informasi dan Ilmu KomputerPerkembangan kejahatan transaksi fraud kartu kredit memberikan dampak kerugian finansial bagi pemegang kartu. Pengembangan model deteksi transaksi fraud menggunakan machine learning telah dilakukan, namun memiliki beberapa tantangan meliputi ...
I Wayan Dharmana +2 more
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Discover Applied SciencesScientific researchers constitute the core strength of innovation within an organization, and their turnover can significantly affect the enterprise. This includes the risk of trade secret disclosure, setbacks in research and development, and stalled ...
Tianyi Zhang +3 more
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Jurnal Teknologi dan Manajemen InformatikaClass imbalance in toddler nutritional status data often reduces the ability of classification models, especially in predicting minority classes. This study aims to analyze the impact of three oversampling techniques, namely SMOTE, WMOTE, and ADASYN, on ...
Naretha Kawadha Pasemah Gumay +5 more
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电力工程技术The insulation performance of transformer bushings is a crucial aspect that directly affects the safe operation of equipment. To diagnose the insulation status of transformer bushings and mitigate the impact of small-sample imbalanced data on diagnostic ...
YANG Hao +5 more
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