Data Mining Technique for Agriculture and Related Areas
Main Article Content
Abstract
Socio-economic factors are the social and economic experiences and realities that help to change one’s attitude, personality, perception and life style. Examples of socio-economic factors are education, experience, age, income, wealth, occupation etc. Farmers’ socio economy is a neglected area due to the emphasis on the level of agricultural productivity. The paper deals with the role of data mining techniques in the field of agriculture and related areas. Some of the most used data mining techniques such as classification; clustering and statistical techniques along with their applications in various domains of agriculture have been discussed. Data mining techniques in the field of agricultural decision making for forecasting agricultural production, quality of production and management are new research areas. This review is conducted to explore the application of data mining in the domains of agriculture for the purpose of finding some efficient technique to improve the socio-economy of the farmers in order to improve the country economy.
Â
Keywords: K-Means clustering, K-Nearest neighbor clustering, Support Vector Machine, Decision Tree.
Downloads
Article Details
COPYRIGHT
Submission of a manuscript implies: that the work described has not been published before, that it is not under consideration for publication elsewhere; that if and when the manuscript is accepted for publication, the authors agree to automatic transfer of the copyright to the publisher.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work
- The journal allows the author(s) to retain publishing rights without restrictions.
- The journal allows the author(s) to hold the copyright without restrictions.