How to increase accuracy of classifiers?
Dimensionality Reduction
Another important procedure is to compare the error rates on training and test dataset to see if you are overfitting (due to the &quot;curse of dimensionality&quot;). E.g., if your error rate on the test dataset is much larger than the error on the training data set, this would be one indicator.
In this case, you could try dimensionality reduction techniques, such as PCA or LDA.
If you are interested, I have written about PCA, LDA and some other techniques here and in my GitHub repo here.
Cross validation
Also you may want to take a look at cross-validation techniques in order to evaluate the performance of your classifiers in a more objective manner