I'm trying to implement a multiclass classification on a 25 features/1300 samples dataset using LinearSVC from sklearn. Unfortunately, my results both on the training and the test sets are very poor (60%). I've tried to optimize the combination of parameters using also GridsearchCV but the results are still the same.
My question is: is there something that I can try in order to improve the performance of the classifier? PCA and standardization? Is it possible that is just this classifier that is not suited to work on the kind of dataset I have? Why could that be?