2012/06/07 by Jay Gholap, Gholap, Jay, Anurag Ingole +7
Computer Science · Environmental Science · Mathematics · #Applications (stat.AP) #Artificial Intelligence (cs.AI) #Data Mining Algorithms and Applications #FOS: Computer and information sciences #Face and Expression Recognition #Machine Learning (stat.ML) #Soil and Land Suitability Analysis #cs.AI #stat.AP #stat.ML
paper · pdf · doi:10.48550/arxiv.1206.1557
4 pages, published in International Journal of Computer Science Issues, Volume 9, Issue 3
arxiv created 2012/06/07 · openalex publication_date 2012/06/07 · arxiv updated 2012/06/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Agricultural research has been profited by technical advances such as automation, data mining. Today, data mining is used in a vast areas and many off-the-shelf data mining system products and domain specific data mining application soft wares are available, but data mining in agricultural soil datasets is a relatively a young research field. The large amounts of data that are nowadays virtually harvested along with the crops have to be analyzed and should be used to their full extent. This research aims at analysis of soil dataset using data mining techniques. It focuses on classification of soil using various algorithms available. Another important purpose is to predict untested attributes using regression technique, and implementation of automated soil sample classification.