So I've got a dataset that looks like:
Weight(KG) Count 25 9 4 17 55 9 4 25 4 7 .... ....
My aim is to find any relation between the
count and maybe predict
count based on a given
I'm using Linear Regression (I don't know if this is the right way to go).
Results were pretty disappointing:
Without label encoding (categorizing) and feature scaling (normalizing) the R squared metric was around 4%. With the encoding and scaling down it 'improved' to 6%.
I'm completely lost as to what model would actually give me some insight into this problem. So my questions are:
- What model would work better for the given data and plot?
- Should I convert the problem into some kind of classification problem and try to predict whether for a given
countis above, say, 20 ?
- Should I try adding in more features and try my luck? If so, would it still be a regression problem?
I'd appreciate any comments on all these questions or even on a single one.
Thanks in advance. Much appreciated.