Detection of Pervasive Developmental Disorder (PDD) Using Naïve Bayes Neural Network Algorithm

• Published in: Proceedings of the International Conference on Cognitive and Intelligent Computing pp. 453 - 459
• Main Authors: Nataraj, K. R., Rakshitha, R., Trupti, Monika, K.
• Format: Book Chapter
• Language: English
• Published: Singapore Springer 2022; Springer Nature Singapore
• Series: Cognitive Science and Technology
• Subjects: Linear regression; Naïve Bayes; Splitting samples; Test dataset; Validation dataset
• ISBN: 9811923493; 9789811923494
• ISSN: 2195-3988; 2195-3996
• DOI: 10.1007/978-981-19-2350-0_44

Autism is defined as neuro developmental disorder which disturbs the behavioral condition and human communication level. This is a situation which is linked with the compound disorder of the brain which can lead to extensive difference in communication, interactivity, and social behavior of victim. We can apply various machine learning algorithms on autism dataset and predict autism at early stage with reducing cost for testing. This paper enables us to realize best neural network algorithm which helps us predict the pervasive developmental disorder using Naïve Bayes neural network algorithm with accuracy and reducing both time and cost for prediction. And this paper also gives the comparison between machine learning algorithms and helps us to know which algorithm gives better output with more accuracy.