Association Rule Data Mining in Agriculture - A Review

被引:3
作者
Vignesh, N. [1 ]
Vinutha, D. C. [1 ]
机构
[1] Vidyavardhaka Coll Engn, Dept Informat Sci & Engn, Mysuru, India
来源
COMPUTATIONAL VISION AND BIO-INSPIRED COMPUTING | 2020年 / 1108卷
关键词
Agriculture; Data mining; Apriori; K-means; K-nearest neighbor;
D O I
10.1007/978-3-030-37218-7_27
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Agriculture is one of the most important occupations carried out by centuries - old people. Agriculture is our nation's backbone occupation. This is actually the occupation that fulfills the people's food needs. In this paper, we examine certain data mining techniques (Association rule) in the field of agriculture. Some of these techniques are explained, such as Apriori algorithm, K-nearest neighbor and K-means and the implementation of these techniques is represented in this field. In this field the effectiveness of the Associative rule is successful. In view of the details of agricultural soils and other data sets, this paper represents the role of data mining (association rule). This paper therefore represents the various algorithms and data mining techniques in agriculture.
引用
收藏
页码:233 / 239
页数:7
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