The analysis of agricultural data with regression data mining technique

Abstract

Data mining is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. This paper discusses data mining technique such as regression and clustering which is a process model for analyzing data and describes the support that SPSS provides for this model. SPSS-based analysis and application construction process is illustrated through a case study in the agricultural domain-ornamental plants. Cluster analysis or clustering was used is the task of assigning a set of objects into groups so that the objects in the same cluster are more similar to each other than to those in other clusters. In this survey clustering technique divides growth factors into several independent categories. Also, regression technique which was used includes many techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps one understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. In this research, analyzed data with regression technique showed the effect of chlorophyll content on the number of flowers.