I have a data set of ~150 samples where for each sample I have 11 inputs and 3 outputs. I tried to build a full regression model to take in 11 inputs to be trained to predict the 3 outputs The issue is with so few samples training a full model is almost impossible. For this reason I am experimenting with regression such as linear regression in pythons sklearn. From what I can find most regression models either support one input to predict one output (after regression is complete) or many inputs to predict one output.
Question: Are there any types of regression that support many inputs to predict many outputs. Or perhaps any regression types at all that may be better suited for my needs.
Thank you for any help!
