# Text Classification Text classification involves assigning predefined categories or labels to text documents. Here are some real-life business use cases for text classification: 1. ***Sentiment Analysis***: Classify customer feedback to identify areas for improvement in product or service. 2. ***Fraud Detection***: Classify the transaction as fraudulent or not based on other features of the text, without explicitly identifying specific entities. 3. ***Topic Categorization***: Automatically sort customer support tickets based on topic to improve response time and efficiency. 4. ***News Article Categorization***: Categorize news articles to monitor trends and stay up-to-date with industry developments. 5. ***Email Filtering***: Identify spam emails to improve email filtering and security. 6. ***Resume Screening***: Classify job resumes to streamline the recruitment process. check how to prepare data for Text Classification task. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.texti.ai/finetuning-task/text-classification.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.