when will the mlp give constant prediction? I have a regression task.(to predict price for finanical market)
I build a mlp to do the regression.
I found mlp will stop at giving a constance prediction. which i think it's useless.
Does this mean, i cant do a better prediction than constant value? but i tried catboost, it give a meaningful prediction.
So, if the mlp give the constant value, is there any common reason? and how to improve that?
This means that your features do  ot have predictive power to estimayevthe target. Hence the MLP has learnt to predict the mean of the target distribution so as to minimize the loss.
Try checking if the constant value is indeed the mean of the target variable.