Data imbalance in autism pre-diagnosis classification systems : an experimental study
Year of publication: |
2020
|
---|---|
Authors: | Abdelhamid, Neda ; Padmavathy, Arun ; Peebles, David ; Thabtah, Fadi ; Goulder-Horobin, Daymond |
Published in: |
Journal of information & knowledge management : JIKM. - Singapore : IKMS, ISSN 0219-6492, ZDB-ID 2225563-1. - Vol. 19.2020, 1, p. 2040014-1-2040014-16
|
Subject: | Autism spectrum disorder | ASD screening | data imbalance | machine learning | undersampling | oversampling | SMOTE | Künstliche Intelligenz | Artificial intelligence | Experiment | Psychische Krankheit | Mental disorder | Klassifikation | Classification |
-
Improving imbalanced machine learning with neighborhood-informed synthetic sample placement
Nasir, Murtaza, (2022)
-
Effects of resampling techniques on imbalanced data classification : a new under-resampling method
Nguyen, Son, (2021)
-
A comparison of resampling techniques for medical data using machine learning
Alahmari, Fahad, (2020)
- More ...
-
Associative Classification Approaches: Review and Comparison
Abdelhamid, Neda, (2014)
-
MAC: A Multiclass Associative Classification Algorithm
Abdelhamid, Neda, (2012)
-
MAC: A Multiclass Associative Classification Algorithm
Abdelhamid, Neda, (2012)
- More ...