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You can perform text classification in two ways: manual or automatic. Manual text classification involves a human annotator, who interprets the content of text and categorizes it ingly. This method can deliver good results but it's time-consuming and expensive.

More formally, text classification is an analytical process that takes any text document as input and assigns a label (or classification) from a predetermined set of class labels.

Text classification is one of the most common tasks in NLP. It is the process of assigning a label or category to a given piece of text. For example, we can classify emails as spam or not spam, tweets as positive or negative, and articles as relevant or not relevant to a given topic.

You can perform text classification in two ways: manual or automatic. Manual text classification involves a human annotator, who interprets the content of text and categorizes it ingly. This method can deliver good results but it's time-consuming and expensive.

Text classification is done in four stages: (a) pre-processing, (b) text representation, (c) feature selection, and finally, (d) classification [19]. The first stage is pre-processing in which the input is cleaned and shaped ing to the need for classification.

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.

Text classification is the process of classifying documents into predefined categories based on their content. It is the automated assignment of natural language texts to predefined categories.

Text Classification Workflow Step 1: Gather Data. Step 2: Explore Your Data. Step 2.5: Choose a Model Step 3: Prepare Your Data. Step 4: Build, Train, and Evaluate Your Model. Step 5: Tune Hyperparameters. Step 6: Deploy Your Model.

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.

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.