Thursday - last edited Thursday
I would like to create and use a predictive model of buy or sell signals for a stock in order to optimize the gain.
For the inputs I created the following table:
Day is the ID
Variation is the daily price variation. I set its role as Attribute.
Indicators are attributes.
Result is equals to 1 if the previous day price variation was positive else 0.
I have created a process like this:
Where I used:
In the Cross Validation I put:
Performance result is not great. Further in another process machine learning memorize the result for a input set.
Could you help me to improve the process?
Thanks in advance
have you tried another learner? E.g. a Random Forest (w/o any (pre)pruning?). I would give this one a try first.