TY  - GEN 
AU  - Martin-Melero, Íñigo
AU  - Serrano Mamolar, Ana
AU  - Rodríguez Diez, Juan José
PY  - 2024
SN  - 979-8-3503-0436-7
SN  - 979-8-3503-0437-4
UR  - https://hdl.handle.net/10259/10902
AB  - The affective computing field usually concerns data that is difficult, expensive or time-consuming to label. One way to overcome this limitation is the application of Semi-Supervised Machine Learning, that typically works with a small set of labeled...
LA  - eng
PB  - IEEE
KW  - Machine learning
KW  - Semi-supervised learning
KW  - Affective computing
KW  - Python
KW  - R
KW  - Aprendizaje automático
KW  - Machine learning
KW  - Emociones y sentimientos
KW  - Emotions
TI  - Evaluation of Semi-Supervised Machine Learning applied to Affective State Detection
DO  - 10.1109/PerComWorkshops59983.2024.10502901
ER  -