Two-dimensional visualization of classification and regression problemsautomatic prediction of behavior from sensory data in autism spectrum disorder

  1. Heba Basheer Saeed Alateyat
Dirigée par:
  1. Manuel Fernández Delgado Directeur/trice
  2. Eva Cernadas García Directeur/trice

Université de défendre: Universidade de Santiago de Compostela

Fecha de defensa: 29 mai 2023

Jury:
  1. Arno Formella President
  2. Pablo García Tahoces Secrétaire
  3. Manisha Sanjay Sirsat Rapporteur

Type: Thèses

Résumé

This thesis formulates methods to perform classification and regression by projecting high-dimensional patterns in two dimensions. These methods create a 2D classification or regression map to visualize the data as a political (for classification) or temperature (for regression) map, where each pixel in the map has an associated prediction. The thesis also uses 26 machine learning models for the automatic prediction of behavior in the treatment of autism spectrum disorder using sensory processing information. Behavior and sensory data are extracted from their respective questionnaires. Out of 11 behavior outcomes, the prediction of externalizing problems is very reliable and accurate enough in other 7 outcomes.