Results 51 to 60 of about 46,171 (307)
Learning Imbalanced Datasets With Maximum Margin Loss
2021 IEEE International Conference on Image Processing (ICIP), 2021 A learning algorithm referred to as Maximum Margin (MM) is proposed for considering the class-imbalance data learning issue: the trained model tends to predict the majority of classes rather than the minority ones. That is, underfitting for minority classes seems to be one of the challenges of generalization.
Haeyong Kang, Thang Vu, Chang D. Yoo
openaire +2 more sources
Adaptation Proposed Methods for Handling Imbalanced Datasets based on Over-Sampling Technique
Al-Mustansiriyah Journal of Science, 2020 Classification of imbalanced data is an important issue. Many algorithms have been developed for classification, such as Back Propagation (BP) neural networks, decision tree, Bayesian networks etc., and have been used repeatedly in many fields.
Liqaa M. Shoohi, Jamila H. Saud
doaj +1 more source
IEEE Access, 2021 A network intrusion detection system (NIDS) is an important technology for cyber security. Recently, machine learning based NIDSs are being actively researched as various machine learning techniques are proposed.
Yeongje Uhm, Wooguil Pak
doaj +1 more source
Superensemble classifier for improving predictions in imbalanced datasets [PDF]
Communications in Statistics: Case Studies, Data Analysis and Applications, 2020 Learning from an imbalanced dataset is a tricky proposition. Because these datasets are biased towards one class, most existing classifiers tend not to perform well on minority class examples. Conventional classifiers usually aim to optimize the overall accuracy without considering the relative distribution of each class.
Tanujit Chakraborty +1 more
openaire +2 more sources
Model Balanced Bagging Berbasis Decision Tree Pada Dataset Imbalanced Class
, 2023 Algoritma klasifikasi merupakan algoritma yang sangat sering digunakan beriringan dengan kebutuhan manusia, namun peneliti an sebelumnya sering dijumpai kendala saat menggunakan algoritma klasifikasi.
Yoga Pristyanto, Aditya Ahmad Zein
core +1 more source
, 2019 A corpus on Bangla newspaper articles created using a custom web crawler containing 12 different topics. The total number of word tokens in this dataset is 28.5+ million.
Anisur Rahman (11489) +1 more
core +4 more sources
Frontiers in Animal Science, 2021 Classification of imbalanced datasets of animal behavior has been one of the top challenges in the field of animal science. An imbalanced dataset will lead many classification algorithms to being less effective and result in a higher misclassification ...
Min Jin +2 more
doaj +1 more source
Active Class Incremental Learning for Imbalanced Datasets [PDF]
, 2020 Accepted in IPCV workshop from ...
Eden Belouadah +3 more
openaire +2 more sources
A Hybrid Sampling SVM Approach to Imbalanced Data Classification
Abstract and Applied Analysis, 2014 Imbalanced datasets are frequently found in many real applications. Resampling is one of the effective solutions due to generating a relatively balanced class distribution.
Qiang Wang
doaj +1 more source
Lightweight Micro-Expression Recognition on Composite Database
Applied Sciences, 2023 The potential of leveraging micro-expression in various areas such as security, health care and education has intensified interests in this area. Unlike facial expression, micro-expression is subtle and occurs rapidly, making it imperceptible.
Nur Aishah Ab Razak, Shahnorbanun Sahran
doaj +1 more source