Skip to content
/ Bangla-Newspaper-Categorization-using-ML-models Public

In my Bangla news categorization project, I utilized XGBoost for efficient pattern recognition, SVM for handling non-linear relationships, and an ensemble of Random Forest, AdaBoost, and Logistic Regression to collectively enhance precision. This diverse approach ensures robust and accurate classification of Bangla news articles.

1 star 0 forks Branches Tags Activity
Star
Notifications You must be signed in to change notification settings

injamul3798/Bangla-Newspaper-Categorization-using-ML-models

BranchesTags

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

4 Commits

Machine learning result.ipynb

Machine learning result.ipynb

 
 

README.md

README.md

 
 

Repository files navigation

Utilizing XGBoost for pattern recognition, SVM for non-linear relationships, and an ensemble of Random Forest, AdaBoost, and Logistic Regression, my Bangla news categorization achieves precision through diverse modeling. This comprehensive approach ensures accurate classification, capturing linguistic nuances and cultural references in Bangla news articles.

Dataset Link: https://www.kaggle.com/datasets/furcifer/bangla-newspaper-dataset/data

Project done by: Md. Injamul Haque && Shakil Rana

About

In my Bangla news categorization project, I utilized XGBoost for efficient pattern recognition, SVM for handling non-linear relationships, and an ensemble of Random Forest, AdaBoost, and Logistic Regression to collectively enhance precision. This diverse approach ensures robust and accurate classification of Bangla news articles.

Topics

nlp sentiment-analysis text-classification svm ml logistic-regression xgboost-classifier adaboostclassifier

Resources

Readme
Activity

Stars

1 star

Watchers

1 watching

Forks

0 forks
Report repository

Releases

No releases published

Packages

No packages published

Contributors 2

  •  
  •  

Languages