title: Classification Precision Optimization towards one class?
body: <p>My dataset has two classes. The one of non-interested takes 90%, and the class of interest is about 10%.</p>
  
  <p>I have already done the resampling, not only once, but a butch of balanced sets (e.g 10 sets). And do the majority vote to get the final prediction results. After compared many models, tree gives the best result. And I have already picked out the most important features based on importance scores.</p>
  
  <p>The overall accuracy is not bad, 75%, but the precision towards the class I am interested is only 30%, which is not good. How to do the optimization towards the precision of the target class? I think the algorithms behind the ctree package in R is to do optimization towards the overall accuracy. I also tried the one-class classification, like svm, but not good. BTW, I used R and python both. But I do not find any relevant packages about my problem. Do I need to write my own tree algorithm which will optimize the precision of the class interested? Thanks.</p>