Which kind of techniques are of better performance for mutli-class classification techniques? Which kind of techniques are suit better with text message classification?

1. the literature review should give an overview of state-of-the art classification techniques with supervised machine learning, e.g. SVM, Navie Bayes, neural network, random forests, decision trees, etc. and summarizes their pros and cons with a table
2. the literature review shall be able to answer the following questions:
questions set a: what are the major steps for classification with supervised machine learning in general? What’s the gap between traditional use case of classification (specify the traditional use case) and text message classification? And therefore, what additional steps are required for text message (e.g. twitter messages or SMS) classification?
questions set b: Which kind of techniques are good in general, which kind of techniques are of better performance for mutli-class classification techniques? Which kind of techniques are suit better with text message classification? …. When writing the overview of each techniques, these questions should be bear in mind, but summarized explicitly in the summarize table as pros and cons.
c. derive a criteria dimension for summarize pros and cons, avoid writing too much text in a table.

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