Exploration of Autism Spectrum Disorder using Classification Algorithms

Data mining plays a vital role in identifying the classification algorithm for classification and prediction of disease in medical field. Predicting disease depends on the accuracy of the dataset and mechanism of machine learning algorithms used to classify the dataset. To detect new born with risk...

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Bibliographic Details
Published in:Procedia computer science 2019, Vol.165, p.143-150
Main Authors: Deepa, B, Jeen Marseline, K.S
Format: Article
Language:English
Subjects:
Autism
Confusion Matrix
Data mining
Decision table
Naive Bayes algorithm
Support Vector Machine
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Summary:Data mining plays a vital role in identifying the classification algorithm for classification and prediction of disease in medical field. Predicting disease depends on the accuracy of the dataset and mechanism of machine learning algorithms used to classify the dataset. To detect new born with risk of autism spectrum disorder (ASD) which is predominantly diagnosing the behavioral observation of children with above 2 years. Although identifying brain disease using magnetic resonance imaging (MRI) available in the last few years it is time consuming and very expensive. Early stage of predicting autism disorder done with the help of using machine learning algorithms. This paper criticize various classification algorithms then evaluates the accuracy and then selects the best classification algorithm to analyze and classify each individual who gets affect from autism spectrum disorder (ASD) in early stage.
ISSN:1877-0509
1877-0509
DOI:10.1016/j.procs.2020.01.098