# Feature addition/ subtraction and SVM model accuracy

I am working on a text classification problem where I would like to improve the accuracy of my model. Presently, I am using SVM with linear SVC and OneVsRestClassifier. The model should correctly predict all of the subcategories for a parent category.

For entered account name, I should get the right description for my test data file that I will use to test the model later.

If I add another feature, +1 or -1, for debit and credit to my Account_Name field, will there any improvement in the accuracy?

Or, is there anything else that will help improve the accuracy of the model?

It is currently at 74% which is low.