Research Area: Machine Learning
Autism Spectrum Disorder (ASD) is on the rise and constantly growing. Earlier identify of ASD with the best outcome will allow someone to be safe and healthy by proper nursing. Humans are hard to estimate the present condition and stage of ASD by measuring primary symptoms. Therefore, it is being necessary to develop a method that will provide the best outcome and measurement of ASD. This paper aims to show several measurements that implemented in several classifiers. Among them, Support Vector Machine (SVM) provides the best result and under SVM, there are also some kernels to perform. Among them, the Gaussian Radial Kernel gives the best result. The proposed classifier achieves 95% accuracy using the publicly available standard ASD dataset.
Keywords:
Support vector machines
Kernel
Logistics
Data mining
Autism
Classification algorithms
Measurement
Author(s) Name: Koushik Chowdhury; Mir Ahmad Iraj
Journal name:
Conferrence name: 2020 International Conference on Recent Trends on Electronics, Information, Communication & Technology
Publisher name: IEEE
DOI: 10.1109/RTEICT49044.2020.9315717
Volume Information: Volume 17
