Results 11 to 20 of about 2,998 (192)

Application of ADASYN and Optuna in the XGBoost Algorithm for Stunting Detection

open access: yesJournal of Applied Informatics and Computing
This 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   +3 more sources

A Ship Trajectory Prediction Method Based on an Optuna–BILSTM Model

open access: yesApplied Sciences
In the field of maritime traffic management, overcoming the challenges of low prediction accuracy and computational inefficiency in ship trajectory prediction is crucial for collision avoidance.
Yipeng Zhou, Ze Dong, Xiongguan Bao
doaj   +3 more sources

Optimizing Multilayer Perceptron for Car Purchase Prediction with GridSearch and Optuna

open access: yesJurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)
Multilayer Perceptron (MLP) is a powerful machine learning algorithm capable of modeling complex, non-linear relationships, making it suitable for predicting car purchasing power. However, its performance depends on hyperparameter tuning and data quality.
Ginanti Riski, Dedy Hartama, Solikhun
doaj   +3 more sources

Federated Hyperparameter Optimisation with Flower and Optuna [PDF]

open access: yesProceedings of the 38th ACM/SIGAPP Symposium on Applied Computing, 2023
Federated learning (FL) is an emerging distributed machine learning technique in which multiple clients collaborate to learn a model under the management of a central server. An FL system depends on a set of initial conditions (i.e., hyperparameters) that affect the system's performance.
Juan Marcelo Parra Ullauri   +4 more
openaire   +3 more sources

Improving Tomato Ripeness Classification Using Knowledge Distillation and Hyperparameter Optimization with Optuna [PDF]

open access: yesJournal of Electrical Engineering and Computer
Automatic classification of tomato ripeness plays a crucial role in ensuring post-harvest quality and efficiency in the horticultural industry. This study proposes a combined strategy of Knowledge Distillation (KD) and hyperparameter optimization using ...
Iasya Sholihin, Andi Sunyoto
doaj   +2 more sources

The Effect of SMOTE and Optuna Hyperparameter Optimization on TabNet Performance for Heart Disease Classification

open access: yesJurnal Sisfokom
Heart 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
doaj   +3 more sources

Optuna Tabanlı Hiper Parametre Optimizasyonu ile Konut Fiyat Tahminlemede Makine Öğrenmesi Tekniklerinin Karşılaştırmalı Analizi

open access: yesGazi Üniversitesi Fen Bilimleri Dergisi
Konut fiyatlarının etkili bir şekilde tahmin edilmesi, ekonominin şekillenmesinde kritik bir rol oynamaktadır. Bu çalışmanın amacı, konut fiyatlarını tahminlemede en iyi performans gösteren makine öğrenmesi modelini belirlemektir.
Vahid Sinap
doaj   +2 more sources

Enhancing Liver Cirrhosis Staging Accuracy using Optuna-Optimized TabNet

open access: yesJournal of Applied Informatics and Computing
Liver cirrhosis is a progressive chronic disease whose early detection poses a clinical challenge, making accurate severity staging crucial for patient management.
Muhammad Farhan Arifin   +4 more
doaj   +2 more sources

Application of the Optuna-NeuralProphet model for predicting step-like landslide displacement

open access: yesAIP Advances
Displacement prediction is crucial to landslide engineering monitoring and early warning. An Optuna-NeuralProphet model is proposed based on the Optuna framework and the NeuralProphet model to address the challenge of predicting step-like landslide ...
Ming Huang, Hougang Yang, Fan Yang
doaj   +2 more sources

Analysis of Gradient Boosting Algorithms with Optuna Optimization and SHAP Interpretation for Phishing Website Detection

open access: yesJournal of Applied Informatics and Computing
Phishing remains a persistent cybersecurity threat, evolving rapidly to bypass traditional blacklist-based detection systems. Machine Learning (ML) approaches offer a promising solution, yet finding the optimal balance between detection accuracy and ...
Rahmat Fauzi Abu Bakar, Majid Rahardi
doaj   +2 more sources

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