Results 91 to 100 of about 2,231 (201)

Analisis Perilaku Remaja Melakukan Seks Pra-Nikah Di Jawa Timur Menggunakan Cart Dengan SMOTE-N-ENN Dan ADASYN-N (Analisis Lanjut SKAP Jawa Timur 2018) [PDF]

open access: yes, 2020
Pembahasan mengenai seks pra-nikah sering dianggap tabu, padahal efek yang ditimbulkan sangat besar. Di Jawa Timur, angka seks pra-nikah pada 2018 naik 1,4%, yakni dari 0,2% menjadi 1,6% (Badan Kependudukan dan Keluarga Berencana Nasional, 2018).
Wening, Kinanthi Sukma
core  

APAROS: A Clustering-Based Hybrid Approach for Handling Overlapped Regions in Imbalanced Datasets

open access: yesIEEE Access
In many real-world datasets, the class distribution is often highly imbalanced, and minority class samples are located within the majority regions, leading to significant overlap.
Annam Nandini   +3 more
doaj   +1 more source

Impact of data balancing a multiclass dataset before the creation of association rules to study bacterial vaginosis

open access: yesIntelligent Medicine
Background: Bacterial vaginosis is a polymicrobial syndrome in which the homeostasis exerted by the Latobacillus species that protect the vaginal mucosa has been lost.
Freddy de la Cruz-Ruiz   +3 more
doaj   +1 more source

HEART DISEASE PREDICTION USING MACHINE LEARNING CLASSIFIERS WITH VARIOUS BALANCING TECHNIQUES [PDF]

open access: yesProceedings on Engineering Sciences
Heart disease or Cardiovascular illness is the most prevalent cause of mortality globally. The challenge of predicting heart illness using clinical data analytics is considerable.
Uzama Sadar   +4 more
doaj   +1 more source

Improvement of Bank Fraud Detection Through Synthetic Data Generation with Gaussian Noise

open access: yesTechnologies
Bank fraud detection faces critical challenges in imbalanced datasets, where fraudulent transactions are rare, severely impairing model generalization. This study proposes a Gaussian noise-based augmentation method to address class imbalance, contrasting
Fray L. Becerra-Suarez   +2 more
doaj   +1 more source

Improving Vehicle Payment Method Classification Using XGBoost with SMOTE and SHAP Interpretation

open access: yesJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Class imbalance in vehicle payment method classification can cause predictive models to become biased toward the majority. This study aims to build a classification model for automotive consumer payment methods using Extreme Gradient Boosting (XGBoost ...
Dedi Trisnawarman, Reza Mahendra
doaj   +1 more source

A cloud‐based hybrid intrusion detection framework using XGBoost and ADASYN‐Augmented random forest for IoMT [PDF]

open access: yes
Internet of Medical Things have vastly increased the potential for remote patient monitoring, data‐driven care, and networked healthcare delivery. However, the connectedness lays sensitive patient data and fragile medical devices open to security threats
Karim SamadZamini   +3 more
core   +1 more source

Predicting coronary artery disease with ensemble-based feature selection and grid search-tuned SVM under class imbalance conditions

open access: yesDiscover Data
Coronary artery disease (CAD) is a common heart condition that leads to numerous deaths. The standard diagnostic tool for CAD, coronary angiography, is expensive, time-consuming, and carries harmful side effects.
Atiyeh Pahlevani   +4 more
doaj   +1 more source

Banking customer churn prediction using random forest based on Smote and Adasyn approach

open access: yesTạp chí Phát triển và Hội nhập
Customer Churn is now becoming a significant problem in the banking sector. It is necessary to seek solutions to predict the rate of customer churn in banks; however, the dataset for customer churn prediction in banks is imbalanced.
Cong Thanh Tran
doaj   +1 more source

Integration of Random Forest, ADASYN, and SHAP for Diabetes Prediction and Interpretation

open access: yesScientific Journal of Informatics
Purpose: Diabetes is a chronic disease with a globally rising prevalence. Early detection of individuals at risk is essential to prevent long-term complications. This study aims to develop a diabetes prediction model that not only achieves high classification accuracy but also provides transparent explanations of the factors influencing its predictions.
Hozana Aulia   +2 more
openaire   +1 more source

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