guidelines for base learner vs stack learner

ThiruThiru Member Posts: 100 Guru
Dear all,  Im working on a classification problem with supervised learning, for which
I want to use the stacking operator to improve accuracy 

1. while choosing stacking operator, im looking for  Is there any guideline how to combine the operators. 
Using Gradient boost alone gives  accuracy 75.75%.  I want to take it beyond 95% using stacking.
 (ofcourse I'll look into the requirements of  precision/recall). 

 I tried many stacking combinations,  i couldnt make it beyond 73%.

2. Any theoretical/white paper reference / rapidminer resource/ book on how to choose the  combination of  base learners , stack learner  for the maximum classification performance.  

3.  will it be useful to use non-neural net operator as base learner & neural net (deep learning ) as stacking learner?
i tried this combination, in my case, it reduces the performance to 55%.
thank you


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