Autor/Autorin: Balakrishna Eppakayala
Dr. Eppakayala Balakrishna completed M.Tech and Ph.D in CSE from JNTU University, Hyderabad. He is working as an Associate Professor in the department of CSE, Vaagdevi College of Engineering.
Mining of Negative Association Rule is helpful to discover the competent items i.e., one item can be substituted for another items in a database. In decision making, we generally use many advantage factors, and also consider some disadvantage factors, for the intention of less-risk (more-profit). It is necessary to focus on Negative Association Rule mining, because in the super market data analysis, Negative Association Rule Mining identifies whatever the items which are not buying together and also whatever the items which may be used as replacing (substituted or alternative) items for other items. Such kind of analysis is possible through Negative Association Rule Mining. Negative rules specify that the relationship between the present and absent item-sets. Negative Association Rule mining is also important because such types of rules should be considered in decision making for applications include product placement and investment analysis.
Balakrishna, EppakayalaDr. Eppakayala Balakrishna completed M.Tech and Ph.D in CSE from JNTU University, Hyderabad. He is working as an Associate Professor in the department of CSE, Vaagdevi College of Engineering.
Über den Autor
Dr. Eppakayala Balakrishna completed M.Tech and Ph.D in CSE from JNTU University, Hyderabad. He is working as an Associate Professor in the department of CSE, Vaagdevi College of Engineering.
Klappentext
Mining of Negative Association Rule is helpful to discover the competent items i.e., one item can be substituted for another items in a database. In decision making, we generally use many advantage factors, and also consider some disadvantage factors, for the intention of less-risk (more-profit). It is necessary to focus on Negative Association Rule mining, because in the super market data analysis, Negative Association Rule Mining identifies whatever the items which are not buying together and also whatever the items which may be used as replacing (substituted or alternative) items for other items. Such kind of analysis is possible through Negative Association Rule Mining. Negative rules specify that the relationship between the present and absent item-sets. Negative Association Rule mining is also important because such types of rules should be considered in decision making for applications include product placement and investment analysis.
