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They can also be classified by their role in the lives of their masters and the work they do. For example, a dog might be a family pet, a working dog, a show dog, or a hunting dog. In many cases, dogs are defined both by their breed and their role. For example, a dog could be a beagle that is a family pet.

Text classification also known as text tagging or text categorization is the process of categorizing text into organized groups. By using Natural Language Processing (NLP), text classifiers can automatically analyze text and then assign a set of pre-defined tags or categories based on its content.

In this classification, there are three main categories: Expository texts. Narrative texts, and. Argumentative texts.

There are many approaches to automatic text classification, but they all fall under three types of systems: Rule-based systems. Machine learning-based systems. Hybrid systems.

Text classification also known as text tagging or text categorization is the process of categorizing text into organized groups. By using Natural Language Processing (NLP), text classifiers can automatically analyze text and then assign a set of pre-defined tags or categories based on its content.

Text classification also known as text tagging or text categorization is the process of categorizing text into organized groups. By using Natural Language Processing (NLP), text classifiers can automatically analyze text and then assign a set of pre-defined tags or categories based on its content.

The Naive Bayes algorithm. Naive Bayes classifiers are a collection of classification algorithms based on Bayes' Theorem. It is not a single algorithm but a family of algorithms where all of them share a common principle, i.e. every pair of features being classified is independent of each other.

You can perform text classification in two ways: manual or automatic....There are many approaches to automatic text classification, but they all fall under three types of systems: Rule-based systems. Machine learning-based systems. Hybrid systems.

Some examples of text classification are: Understanding audience sentiment from social media, Detection of spam and non-spam emails, Auto tagging of customer queries, and. Categorization of news articles into defined topics.

How To Categorize User Comments? NLP. Sentiment Analysis. Text Classification. Topic Tagging. Word Association.