Results 21 to 30 of about 1,984 (174)
Technologies, 2023 This paper explores the application of various machine learning techniques for predicting customer churn in the telecommunications sector. We utilized a publicly accessible dataset and implemented several models, including Artificial Neural Networks ...
Mehdi Imani, Hamid Reza Arabnia
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Jurnal SisfokomHeart disease is a medical condition affecting the cardiovascular system, disrupting blood circulation and reducing cardiac function efficiency, which can lead to severe health complications.
Danang Wijayanto +3 more
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Enhancing Hypertension Risk Assessment Through Machine Learning Models [PDF]
EPJ Web of ConferencesHypertension is also a significant health issue in the world that needs precise early risk prediction mechanisms. The present study suggests an improved ensemble-based machine learning model combining XGBoost, LightGBM, and CatBoost classifiers with the ...
Avinash Y. B. +4 more
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An Optimized Hyperparameter Tuning for Improved Hate Speech Detection with Multilayer Perceptron
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)Hate speech classification is a critical task in the domain of natural language processing, aiming to mitigate the negative impacts of harmful content on digital platforms.
Muhamad Ridwan, Ema Utami
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NTU Journal of Engineering and TechnologyAlzheimer's Disease (AD) is considered one of the most prevalent neurological disorders, primarily affecting elderly people and adversely impacting their brain functions. This disease is characterized by the gradual deterioration of cognitive functions,
Nawzt Sadiq Jaafar Al-Bayati +1 more
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Advanced Engineering Materials, EarlyView.This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer +4 more
wiley +1 more source
Continual Learning for Multimodal Data Fusion of a Soft Gripper
Advanced Robotics Research, EarlyView.Models trained on a single data modality often struggle to generalize when exposed to a different modality. This work introduces a continual learning algorithm capable of incrementally learning different data modalities by leveraging both class‐incremental and domain‐incremental learning scenarios in an artificial environment where labeled data is ...
Nilay Kushawaha, Egidio Falotico
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Optimization of diabetes prediction methods based on combinatorial balancing algorithm
Nutrition & DiabetesBackground Diabetes, as a significant disease affecting public health, requires early detection for effective management and intervention. However, imbalanced datasets pose a challenge to accurate diabetes prediction.
HuiZhi Shao +3 more
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ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
Advanced Science, EarlyView.The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Journal of Applied Informatics and ComputingThis study aims to evaluate the effectiveness of three hyperparameter optimization approaches Random Search, Successive Halving, and Optuna in the CatBoost algorithm for modeling individual income using the 2024 SAKERNAS data.
Claudian Tikulimbong Tangdilomban +2 more
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