Classify Text License For Free

Text categorization (a.k.a. text classification) is the task of assigning predefined categories to free-text documents. It can provide conceptual views of document collections and has important applications in the real world.

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.

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.

What is Text Classification? Text classification is a machine learning technique that assigns a set of predefined categories to open-ended text. Text classifiers can be used to organize, structure, and categorize pretty much any kind of text from documents, medical studies and files, and all over the web.

Categorization in text mining means sorting documents into groups. Automatic document classification uses a combination of natural language processing (NLP) and machine learning to categorize customer reviews, support tickets, or any other type of text document based on their contents.

What is Text Classification? Text classification is a machine learning technique that assigns a set of predefined categories to open-ended text. Text classifiers can be used to organize, structure, and categorize pretty much any kind of text from documents, medical studies and files, and all over the web.

This dataset includes the text of SMS messages along with a label indicating whether the message is unwanted. Junk messages are labeled spam, while legitimate messages are labeled ham.