Which classifier is more accurate for a SVM classification?
You should take a look at Feature selection and algorithms that automate this process. It's okay if you are new to ML and don't understand the entire feature selection process, just get the proper intuition and then you can use a library to automate the process.

The key idea of having a Learning algorithm is so that it can find the patterns ... the most you can do, is help him out by providing lots of (non-redundant) data and having a good preprocessing step, that usually involves stuff like feature selection, and normalization.

On a friendly note, when implementing learning algorithms, you should not try to modify your dataset just by 'looking' at it, unless you have concrete metrics that testifies it needs modifications, many a  times, it has been the case, that the learning algorithm put high bias towards features that did not appear to be even remotely 'related' to the classification process. Always try to do a feature selection step before trying any modifications on your data.