text: Title: Reduce RAM and ROM footprint
  Body: I'm using `m2cgen` to convert some classifier to C. It works great and results are consistent, thanks for the library!
  
  1. I have the problem that the compiled binaries are too large to fit on my embedded  device. I checked and the binaries are around double the size of the binaries created with e.g [`sklearn_porter`](https://github.com/nok/sklearn-porter). However, `m2cgen` is the only libraries that can convert my python classifiers to C without introducing errors into the classification.
  2. Even if I reduce the size of the classifier, I run into the problem that the RAM of the device is exceeded (think of something in the kB range).
  
  Do you have any idea how the footprint of the c code could be reduced?