An Effective Model Of Autism Spectrum Disorder Using Machine Learning

Autism spectrum disorder (ASD) is one of the most common diseases that affect human nerves and cause a decrease in intelligence comprehension person. This disease group various disorders are characterized by poor social behavior communication. It affects all age groups, including adults, adolescents, children, elderly, but symptoms this always appear their early years. ASD suffer from problems, important which data loss, low quality, extreme values. makes process diagnosing early. Our goals research to solve problems. The cussent authors proposed technical model solves We used ensemble techniques include Bayesian Boosting, Classification Regression, Polynomial Binominal Classification. also classification CHAID, Decision Stump, Tree (Weight-Based), Gradient Boosted Trees, ID3. proven has obtained highest search accuracy reached 100% as well we have f1 measurement 100%. proves our work superior its peers.