Two-dimensional visualization of classification and regression problemsautomatic prediction of behavior from sensory data in autism spectrum disorder
- Heba Basheer Saeed Alateyat
- Manuel Fernández Delgado Zuzendaria
- Eva Cernadas García Zuzendaria
Defentsa unibertsitatea: Universidade de Santiago de Compostela
Fecha de defensa: 2023(e)ko maiatza-(a)k 29
- Arno Formella Presidentea
- Pablo García Tahoces Idazkaria
- Manisha Sanjay Sirsat Kidea
Mota: Tesia
Laburpena
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.