What is a better solution for text classification than use of perplexity To classify some texts, I train a language model over a training set and then select the model which has the lowest perplexity on a given test sample as the class of that sample. 
I would like to know what other methods or measures except perplexity can be used.
You can evaluate pre-built language models. Advantage is :


These models are usually trained on very large text corpora (Such a a snapshot of  text from billions of Web pages). 
It requires very little development effort for testing models for a given classification problem. 


Examples :

https://spacy.io/usage/examples

https://uber.github.io/ludwig/examples/