On Effectively Predicting Autism Spectrum Disorder Using an Ensemble of Classifiers

TL;DR

This study evaluates ensemble classifier systems for early autism spectrum disorder detection, demonstrating that multiple classifier ensembles, especially with three classifiers, outperform individual classifiers in predictive accuracy.

Contribution

The paper introduces an evaluation of various ensemble learning methods for ASD prediction using behavioral and therapy data, highlighting the effectiveness of bagging and boosting techniques.

Findings

Multiple classifier ensembles outperform single classifiers in ASD prediction.

Ensembles with three classifiers yield the best performance.

Social communication gestures are key factors in ASD detection.

Abstract

An ensemble of classifiers combines several single classifiers to deliver a final prediction or classification decision. An increasingly provoking question is whether such systems can outperform the single best classifier. If so, what form of an ensemble of classifiers (also known as multiple classifier learning systems or multiple classifiers) yields the most significant benefits in the size or diversity of the ensemble itself? Given that the tests used to detect autism traits are time-consuming and costly, developing a system that will provide the best outcome and measurement of autism spectrum disorder (ASD) has never been critical. In this paper, several single and later multiple classifiers learning systems are evaluated in terms of their ability to predict and identify factors that influence or contribute to ASD for early screening purposes. A dataset of behavioural data and robot-enhanced therapy of 3,000 sessions and 300 hours, recorded from 61 children are utilised for this task. Simulation results show the superior predictive performance of multiple classifier learning systems (especially those with three classifiers per ensemble) compared to individual classifiers, with bagging and boosting achieving excellent results. It also appears that social communication gestures remain the critical contributing factor to the ASD problem among children.