Textual Classification

Textual Classification

Classification is the process of predicting the class of given data points. Classes are referred to as targets/ labels or categories. Classification belongs to the category of supervised learning.

There are two types of learning techniques in Classification –

  • Lazy Learning
  • Eager Learning

Textual Classification

Textual classification is one of the basic tasks in Natural Language Processing (NLP).

It is a technique used to organize, structure, and categorize textual content like documents, reports, emails, website content, and files.

Textual classification finds a wide range of applications in areas like sentiment analysis, spam detection, and labeling of information.

Example:

  • News snippets can be classified according to sports, business, entertainment, and politics.
  • Brand reviews can be classified according to positive, negative, and neutral sentiments.
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