Predicting Personalized Quality of Life of an Intellectually Disabled Person Utilizing Machine Learning

This work aims to enhance dependent persons’ quality of life (QOL) by examining various aspects their lives and providing the required assistance each aspect QOL. We employ machine learning methods evaluate eight QOL forecast corresponding index value. Machine algorithms input predict The Index value says requirement support a person, it depends on use our dataset train model. Dataset is collected using GENCAT scale tool, which takes 69 items provides score for apply many linear nonlinear regression algorithms. multiple algorithm results show better performance root mean squared error (1.4729) R2 (0.9918).