I am new to R and Machine Learning, and I am hopeful that you can assist me with the issue I am facing. I have been endeavoring to employ Artificial Neural Networks (ANNs) for filling missing data in the target variable (T1), which has corresponding predictor variables, namely P1, P2, P3, P4, and P5.
My objective is to predict the target variable across the time period for which predictor variable data is available. I tried and excluded the "missing" months from the training and testing datasets to construct the model, which I subsequently use to predict these absent months. Nevertheless, I am uncertain whether my approach is correct or not because the model performance is very low and not improving.
Do any of you have example code or practical experience with gap-filling datasets that could guide me in addressing this issue? I have been stuck on this problem for a few months now, and I am hoping that your insightful guidance will help me overcome this hurdle.
Thank you for your assistance.