What is stratified k-fold cross-validation? What is hyperparameter tuning in text classification?

Dec 24, 2018 ... This workflow demonstrates how tidy data principles can be used not just for data cleaning and munging, but for sophisticated machine learning as well. Text classification also known as text tagging or text categorization is the process of assigning tags/labels to unstructured text. Using Natural Language ... Abstract. Bidirectional Encoder Representations from Transformers (BERT) and BERT-based approaches are the current state-of-the-art in many natural language ... Mar 29, 2025 ... We explore the application of LLMs to supervised text classification. As a case study, we consider stance detection and examine variation in predictive ... Jun 5, 2023 ... In this blog post, we'll present seven powerful text classification techniques to fit all these situations. 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 ... SST-2 Binary text classification with XLM-RoBERTa model. Author: Parmeet Bhatia. Overview. This tutorial demonstrates how to train a text classifier on ... In natural language processing (NLP), text classification tasks are increasingly fine-grained, as datasets are fragmented into a larger number of classes ... Dec 24, 2022 ... In this post we'll see a demonstration of an NLP-Classification problem with 2 different approaches 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 ...