TY - JOUR
T1 - A Novel Approach to Predict the Early Childhood Special Education Learning Skills of Autistic Children Using Ensemble Machine Learning
AU - Ocaña-Fernández, Yolvi J.
AU - Gómez-Gonzales, Walter
AU - Valenzuela Fernández, Luis Alex
AU - Vásquez Ramos, Segundo Pio
AU - Dueñas Zúñiga, Huguette Fortunata
AU - Huaman Fernandez, Jackeline Roxana
AU - Amapanqui Broncano, Marco Antonio
N1 - Publisher Copyright:
© 2023, Innovative Information Science and Technology Research Group. All rights reserved.
PY - 2023/6
Y1 - 2023/6
N2 - Children with autism spectrum disorder will eventually receive more extensive educational experiences, diverse understanding styles, any distinctive instructional techniques to help all infants achieve. Data mining categorization algorithms in the Weka tool are used to anticipate and forecast infants' performance with Autism Spectrum Disorder (ASD). As a decision-making tool for improving the performance of autistic youngsters, data mining is widely acknowledged. Support Vector Machines (SVMs), Logistic Regression (LR), and Naive Bayes (NB) are some of the techniques that can be used for categorization. The categorization model's outcomes include information on the model's accuracy, error rate, confusion matrices, classifier effectiveness, and execution time.
AB - Children with autism spectrum disorder will eventually receive more extensive educational experiences, diverse understanding styles, any distinctive instructional techniques to help all infants achieve. Data mining categorization algorithms in the Weka tool are used to anticipate and forecast infants' performance with Autism Spectrum Disorder (ASD). As a decision-making tool for improving the performance of autistic youngsters, data mining is widely acknowledged. Support Vector Machines (SVMs), Logistic Regression (LR), and Naive Bayes (NB) are some of the techniques that can be used for categorization. The categorization model's outcomes include information on the model's accuracy, error rate, confusion matrices, classifier effectiveness, and execution time.
KW - ASD
KW - Diagnosis
KW - Learning Disabilities
KW - Logistic Regression (LR) and SVM
KW - Multinomial NB
UR - http://www.scopus.com/inward/record.url?scp=85165723678&partnerID=8YFLogxK
U2 - 10.58346/JOWUA.2023.I2.005
DO - 10.58346/JOWUA.2023.I2.005
M3 - Artículo
AN - SCOPUS:85165723678
SN - 2093-5374
VL - 14
SP - 59
EP - 65
JO - Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications
JF - Journal of Wireless Mobile Networks, Ubiquitous Computing, and Dependable Applications
IS - 2
ER -