dayyass/text-classification-baseline
Pipeline for fast building text classification TF-IDF + LogReg baselines.
This tool helps you quickly build a text classification model without writing custom code. You provide a CSV file with text and a corresponding category (like 'spam' or 'not spam', or 'urgent' and 'low priority'). The tool then outputs a trained model that can automatically classify new text, along with a mapping of your original categories. It's for data scientists or analysts who need to categorize large amounts of text efficiently.
No commits in the last 6 months. Available on PyPI.
Use this if you need a fast and straightforward way to categorize text data into predefined groups, using a proven baseline method.
Not ideal if you require advanced neural network models, highly customized natural language processing pipelines, or need to handle very complex linguistic nuances beyond what TF-IDF and Logistic Regression offer.
Stars
62
Forks
4
Language
Python
License
MIT
Category
Last pushed
Nov 06, 2021
Commits (30d)
0
Dependencies
7
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/dayyass/text-classification-baseline"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
castorini/hedwig
PyTorch deep learning models for document classification
AnubhavGupta3377/Text-Classification-Models-Pytorch
Implementation of State-of-the-art Text Classification Models in Pytorch
inspirehep/magpie
Deep neural network framework for multi-label text classification
kk7nc/Text_Classification
Text Classification Algorithms: A Survey
InseeFrLab/torchTextClassifiers
A unified framework for text classification in PyTorch.