Results 171 to 180 of about 2,231 (201)

MIAC: Mutual-Information Classifier with ADASYN for Imbalanced Classification

2018 International Conference on Security, Pattern Analysis, and Cybernetics (SPAC), 2018
currently, classification of imbalanced data is a significant issue in the area of data mining and machine learning because of the imbalance of most of the data set. An effective solution of this problem is Cost-Sensitive Learning (CSL), but when the costs are not given, this method cannot work property.
Yanyu Cao, Xiaodong Zhao, Zhiping Zhou, Yufei Chen 0002, Xianhui Liu, Yongming Lang   +5 more
openaire   +1 more source

Enhancing Students’ Academic Performance Classifier using ADASYN and MLP

2024 IEEE 22nd Student Conference on Research and Development (SCOReD)
Fairul Nazmie Osman, Mohd Nasir Taïb
exaly   +2 more sources

The Impact of SMOTE and ADASYN on Random Forest and Advanced Gradient Boosting Techniques in Telecom Customer Churn Prediction [PDF]

This paper explores the capability of various machine learning algorithms, including Random Forest and advanced gradient boosting techniques such as XGBoost, LightGBM, and CatBoost, to predict customer churn in the telecommunications sector.
Ali Beikmohammadi, Majid Joudaki, Mehdi Imani   +2 more
exaly   +2 more sources

SMOTE vs. ADASYN

Significant technical progress has led to an expansion in human requirements. As a result, the banking sector has seen a rise in the quantity of loan approval requests. When choosing a candidate for loan approval, a number of factors are taken into account to determine the loan's status.
Sabyasachi Pramanik, Soma Bag, Atanu Roy, Ramkrishna Ghosh, Pranati Rakshit   +4 more
openaire   +1 more source

An advancement in AdaSyn for imbalanced learning: An application to fraud detection in digital transactions

Journal of Intelligent & Fuzzy Systems
Imbalanced Learning is a significant issue in machine learning, affecting the performance and accuracy of binary or multi-classification algorithms, especially in large-scale data handling and classification. There are some popular techniques to covert this imbalanced data into a balanced one such as undersampling, under-sampling with tomek links ...
Chandana Gouri Tekkali, Karthika Natarajan   +1 more
openaire   +1 more source

Multiclass Imbalanced Handling using ADASYN Oversampling and Stacking Algorithm

2022 16th International Conference on Ubiquitous Information Management and Communication (IMCOM), 2022
Yoga Pristyanto, Anggit Ferdita Nugraha, Akhmad Dahlan, Lucky Adhikrisna Wirasakti, Aditya Ahmad Zein, Irfan Pratama   +5 more
openaire   +1 more source

Fault Diagnosis of INFO-SVM Transformer Based on ADASYN

2023 3rd International Conference on Electrical Engineering and Control Science (IC2ECS), 2023
Xin Feng, Weili Wu
openaire   +1 more source

A comparative study of SMOTE and ADASYN for multiclass classification of IoT anomalies

International Journal on Information Technologies and Security
The rise of IoT technologies has increased the need for robust threat detection to address growing cyber-physical risks. Traditional machine learning (ML) models often struggle with imbalanced datasets, particularly in detecting rare threats. This study tackles this challenge using the "IoT_Modbus" dataset, a benchmark for multiclass cybersecurity ...
openaire   +1 more source

Deep Learning Approach Based on ADASYN for Detection of Web Attacks in the CICIDS2017 Dataset

Lecture Notes in Networks and Systems, 2022
Amit Mahajan, Vibhakar Mansotra, Mansotra Vibhakar   +2 more
exaly  

ADASEML: Hospitalization Period Prediction of COVID-19 Patients Using ADASYN and Stacking Based Ensemble Learning

Communications in Computer and Information Science, 2023

exaly