Open AccessData Mining Approach For Exploring Soil Fertility
Author(s) -
Sneha Sehrawat
Publication year - 2022
Publication title -
indian scientific journal of research in engineering and management
Language(s) - English
Resource type - Journals
ISSN - 2582-3930
DOI - 10.55041/ijsrem11833
Subject(s) - cluster analysis , field (mathematics) , computer science , data mining , agriculture , production (economics) , support vector machine , precision agriculture , k means clustering , yield (engineering) , machine learning , data science , mathematics , geography , materials science , archaeology , metallurgy , pure mathematics , economics , macroeconomics
Predication of crop is a widespread problem . Farmer always had a curiosity to know his yield production, climatic condition, how the yield will be better. Simplifying the agriculture production is the essentiality of agriculture improvement. There is need to develop good techniques for crop prediction and other related aspects. Data mining has been emerged a great field in the agriculture. Data mining enables farmers to identify potentially interesting and unknown patterns in large volume of datasets. This paper discuss about the techniques of data mining that helps the farmers to overcome the problems and provide a suitable solution to them. Keywords:- Data mining , Clustering , Bi -Clustering , K-Nearest Method , Support Vector Machines(SVMs)