Sentence classification
Sentence classification deals with understanding text found in natural languages and determining the classes that it may belong to. In the text classification set of problems, you will have a set of documents d that belongs to the corpus X (which contains all the documents). You will also have a set of finite classes C = {c1 , c2, ..., cn}. Classes are also called categories or labels. To train a model, you would need a classifier, which is generally a well-tested algorithm (not necessary but in this case we will be talking about a well-tested algorithm that is used in fastText) and you will need a corpus with documents and associated labeling identifying the classes that each document belongs to.
Text classification has many practical uses, such as the following:
- Creating spam classifiers in email
- Page ranking and indexing in search engines
- Sentiment detection in reviews that will give an idea whether customers are happy with the product or not
Text classification...