Comparison Analysis of Nepali News Classifier

Authors

  • Koshish Shrestha Dept. of Computer Engineering, Kathmandu Engineering College
  • Kabita Khanal Dept. of Computer Engineering, Kathmandu Engineering College
  • Isha Shrestha Dept. of Computer Engineering, Kathmandu Engineering College
  • Neerav Shrestha Dept. of Computer Engineering, Kathmandu Engineering College\
  • Kunjan Amatya Assoc. Professor, Computer Engineering, Kathmandu Engineering College

DOI:

https://doi.org/10.3126/kjse.v9i1.78347

Keywords:

Nepali news, News Classification, Machine Learning, Logistic Regression, Random Forest Algorithm, Neural Network, Categories, Training, Testing, Efficiency

Abstract

With the growing volume of daily generated Nepali news content, which predominantly exists in unstructured formats, the need arises to effectively categorize and label this information. Considering this challenge, our system employs various Machine Learning algorithms such as Logistic Regression, Random Forest Algorithm, Neural Networks, etc., to automatically classify Nepali news into predefined categories and evaluate the efficiency of the model, which offers us a comparative analysis of these various algorithms.

Downloads

Download data is not yet available.
Abstract
130
PDF
88
Cover KJSE

Downloads

Published

2025-05-07

How to Cite

Koshish Shrestha, Kabita Khanal, Isha Shrestha, Neerav Shrestha, & Kunjan Amatya. (2025). Comparison Analysis of Nepali News Classifier. KEC Journal of Science and Engineering, 9(1), 52–58. https://doi.org/10.3126/kjse.v9i1.78347

Issue

Vol. 9 No. 1 (2025)

Section

Articles