Results 61 to 70 of about 39,918 (213)

Comparison of Elliptic Envelope Method and Isolation Forest Method on Imbalance Dataset [PDF]

, 2020
Supri Bin Hj Amir, Bagas Prasetyo
openalex   +1 more source

Posterior Re-calibration for Imbalanced Datasets

, 2020
Accepted to NeurIPS ...
Tian, Junjiao, Liu, Yen-Cheng, Glaser, Nathan, Hsu, Yen-Chang, Kira, Zsolt   +4 more
openaire   +2 more sources

Review of Class Imbalance Dataset Handling Techniques for Depression Prediction and Detection

, 2023
Simisani Ndaba
openalex   +2 more sources

Time Series Classification Using Convolutional Neural Network On Imbalanced Datasets [PDF]

, 2021
Syed Rawshon Jamil
openalex   +1 more source

Enhancing Medicare Fraud Detection Through Machine Learning: Addressing Class Imbalance With SMOTE-ENN

IEEE Access
The healthcare fraud detection field is constantly evolving and faces significant challenges, particularly when addressing imbalanced data issues. Previous studies mainly focused on traditional machine learning (ML) techniques, often struggling with ...
Rayene Bounab, Karim Zarour, Bouchra Guelib, Nawres Khlifa   +3 more
doaj   +1 more source

An Efficient Deep Learning-Based Skin Cancer Classifier for an Imbalanced Dataset. [PDF]

Diagnostics (Basel), 2022
Alam TM, Shaukat K, Khan WA, Hameed IA, Almuqren LA, Raza MA, Aslam M, Luo S.   +7 more
europepmc   +1 more source

Proposal of self and semi-supervised learning for imbalanced classification of coronary heart disease tabular data

Tecnología en Marcha
Triple Mixup is an augmentation policy in the hidden latent space we introduced in the Contrastive Mixup Self-Semi Supervised learning framework, to address the imbalanced data problem, for Cardiovascular Heart Diseases tabular dataset. Medical tabular
Danny Xie-Li, Manfred González-Hernández   +1 more
doaj   +1 more source

The Imbalanced Target Classification Method Based on Mixed Learning of Virtual and Real Data

IEEE Access
We proposes a category imbalance classification model based on mixed feature enhancement between virtual and real domains to address the class imbalance problem in maritime target classification applications.
Fengyu Yang, Peng Wang, Wutao Qin, Zhangze Liao   +3 more
doaj   +1 more source

Class-Aware Fish Species Recognition Using Deep Learning for an Imbalanced Dataset. [PDF]

Sensors (Basel), 2022
Alaba SY, Nabi MM, Shah C, Prior J, Campbell MD, Wallace F, Ball JE, Moorhead R.   +7 more
europepmc   +1 more source

Exploiting Synthetically Generated Data with Semi-Supervised Learning\n for Small and Imbalanced Datasets [PDF]

, 2019
María Pérez‐Ortiz, Peter Tiňo, Rafał Mantiuk, César Hervás‐Martínez   +3 more
openalex   +1 more source