Impact of Data Balancing and Feature Selection on Machine Learning-based Network Intrusion Detection
JOIV: International Journal on Informatics Visualization, 2023 Unbalanced datasets are a common problem in supervised machine learning. It leads to a deeper understanding of the majority of classes in machine learning.
Azhari Shouni Barkah +3 more
doaj +1 more source
Classification results of proposed ER-VC model for binary classification on ADASYN-balanced data. [PDF]
, 2022 Classification results of proposed ER-VC model for binary classification on ADASYN-balanced data.
Furqan Rustam (10196722) +6 more
core +1 more source
Research on hybrid intrusion detection method based on the ADASYN and ID3 algorithms
Mathematical Biosciences and Engineering, 2021 <abstract> <p>Intrusion detection system plays an important role in network security. Early detection of the potential attacks can prevent the further network intrusion from adversaries. To improve the effectiveness of the intrusion detection rate, this paper proposes a hybrid intrusion detection method that utilizes ADASYN (Adaptive ...
Yue Li +4 more
openaire +3 more sources
Mortality Prediction from Hospital-Acquired Infections in Trauma Patients Using an Unbalanced Dataset [PDF]
Healthcare Informatics Research, 2020 Objectives Machine learning has been widely used to predict diseases, and it is used to derive impressive knowledge in the healthcare domain. Our objective was to predict in-hospital mortality from hospital-acquired infections in trauma patients on an ...
Mehrdad Karajizadeh +4 more
doaj +1 more source
Applied Sciences, 2021 The problem of imbalanced datasets is a significant concern when creating reliable credit card fraud (CCF) detection systems. In this work, we study and evaluate recent advances in machine learning (ML) algorithms and deep reinforcement learning (DRL ...
Tran Khanh Dang +3 more
doaj +1 more source
Komparasi metode SMOTE dan ADASYN dalam meningkatkan performa klasifikasi herregistrasi mahasiswa baru [PDF]
, 2021 Perguruan tinggi setiap tahunnya melakukan penerimaan mahasiswa baru pada awal tahun ajaran baru. Dalam penerimaan calon mahasiswa baru jalur SPAN PTKIN di UINSA banyak calon mahasiswa yang tidak melakukan daftar ulang akan berdampak kepada pendapatan ...
Nurdian, Risky Agung
core
Results of the learning models using ADASYN upsampled. [PDF]
Results of the learning models using ADASYN upsampled.
Raafat M. Munshi (17768876)
core +1 more source
Impact of Adaptive Synthetic on Naïve Bayes Accuracy in Imbalanced Anemia Detection Datasets
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)This research aims to analyze the impact of the Adaptive Synthetic (ADASYN) oversampling technique on the performance of the Naïve Bayes classification algorithm on datasets with class imbalance.
Muhammad Khahfi Zuhanda +4 more
doaj +1 more source
An Efficient SMOTE-Based Deep Learning Model for Voice Pathology Detection
Applied Sciences, 2023 The Saarbruecken Voice Database (SVD) is a public database used by voice pathology detection systems. However, the distributions of the pathological and normal voice samples show a clear class imbalance.
Ji-Na Lee, Ji-Yeoun Lee
doaj +1 more source
Multi-Label Opinion Mining Based on Random Forest with SMOTE and ADASYN
CompilerMulti-label classification is essential to categorize data into multiple labels simultaneously. However, data imbalance poses a challenge, where some labels have much less representation, thus reducing the model performance.
Ricy Ardiansyah +2 more
doaj +1 more source