A Study on the use of Agriculture Data Mining

EasyChair Preprint 2458

Abstract

In this paper, we study various review papers on use of data mining in the field of agriculture. Researches have used various data mining techniques, machine learning methods to real life agricultural datasets to very positive conclusions. Most of the papers concluded the results from application of data mining much more accurate compared to even experts. There researchers have used techniques like ID3 decision tree, Optimization algorithms, Bayesian classification, WEKA, Clustering techniques, MBA algorithms and many others. One if the biggest challenges faced by the researchers is the dataset itself. The dataset available in the field of agriculture is unclean. The datasets come with lot of missing values, duplicate entries and many other wide differences requiring multiple efforts in cleaning of data itself though many researches used this challenge as an opportunity as well to use data mining techniques to arrive to a usable dataset

Keyphrases: Agriculture, Clustering, algorithm

@booklet{EasyChair:2458,
  author    = {Vyoma Srivastava and Vishnu Sharma and Dr.Abhay Srivastava},
  title     = {A Study on the use of Agriculture Data Mining},
  howpublished = {EasyChair Preprint 2458},
  year      = {EasyChair, 2020}}