Scopus Indexed Publications

Paper Details


Title
A Systematic Analysis for Machine Learning Based Cow Price Prediction
Author
A. K. M. Tasnim Alam, Afrin Jahan Urme, Rashidul Hasan Hridoy, Zahid Hasan Nirob,
Email
Abstract

Cow meets a significant number of demands for meats in South Asian countries, and a huge number of cows were sold in Bangladesh on the eve of Eid al-Adha. Cow prices depend on several factors, and determining the price of a cow is a cumbersome task for an inexperienced individual. Nowadays machine learning algorithms are significantly used for accurate price estimation. This study presents an efficient and accurate tool for determining cow prices using several characteristics of cows based on machine learning. Sixteen characteristics of a cow are considered in this study to determine its price. Four different machine learning algorithms were used and evaluated in this study for generating an accurate price prediction model. In this machine learning based systematic analysis, several experimental studies are conducted for evaluating models more precisely. Performance matrices were also used to evaluate machine learning algorithms.


Keywords
"Systematic analysis cow price prediction machine learning gradient boosting regression decision tree regression random forest regression linear regression"
Journal or Conference Name
Lecture Notes in Business Information Processing
Publication Year
2023
Indexing
scopus