What is Hugging Face Transformers? How to implement text classification using scikit-learn?

In text classification, we are given a description $\onedoc \in \mathbb{X}$ of a document, where $\mathbb{X}$ is the document space ; and a fixed set of ... In this article, I will explain about the text classification and the step by step process to implement it in python. Oct 28, 2013 ... Text categorization ... Text categorization (a.k.a. text classification) is the task of assigning predefined categories to free-text documents. It ... Oct 13, 2016 ... Multilingual Text Classification (MLTC) is a text classification task in which documents are written each in one among a set L of natural ... May 1, 2020 ... We hypothesize that the application of different combinations of preprocessing methods can improve TC results. Aug 9, 2024 ... This study aimed to evaluate their performances on social media-based health-related text classification tasks. ... classification operation. Currently, the only available key is: task_description : A string containing a short explanation of the text classification task. Abstract. This article offers an empirical exploration on the use of character-level convolutional networks (ConvNets) for text classification. We constructed ... This example shows how to incrementally train a model to classify documents based on word frequencies in the documents; a bag-of-words model. Nov 16, 2023 ... Looking for a very small text classification transformer [R]. Research. I'm looking for suggestions for a transformer model that I can fine-tune ...