following this question, I'm making a data analysis again because I tried to use machine learning algorithms like Random forest to predict a value from certain features but it didn't work for me. I also tried Neural Networks and the results were worse than Random Forest.
So I thought maybe is something wrong with my data as I also read that data can have bad quality somehow(I'm not sure what does this mean). Since I'm not a data scientist and don't have background in Data Science in general (I'm an Electrical Engineer), I want to ask here and maybe someone can help me.
I read that correlation between features and target that I want to predict is important, now this is not my case, my features doesn't have a strong correlation with my features, does this mean that my data is bad and I can't predict that target from those features ?
my target that I want to predict is xdistance and ydistance. It have negative correlation with one another but I think it is not important since I'm predicting every target on its own, but what is interesting here is that there is no feature that correlate strongly with one of the two targets. So I fear that this is an impossible task to try to predict those targets, am I right?