Discovering potential patterns from complex data is a hot research topic. In this paper, the author proposes an iterative
data mining model based on "Interval-Value" clustering, "Interval-Interval" clustering, and "Interval-Matrix" clustering.
"Interval-Value" clustering uses the features of interval data and digital threshold and designed by "Netting"→ "Type-I
clustering"→"Type-II clustering"; "Interval-Interval" clustering uses the features of interval data and interval threshold and
designed with interval medium clustering; "Interval-Matrix" clustering uses the features of interval data and matrix
threshold and designed by matrix threshold clustering. Motivation of the author is to mine the interval-valued association
rules for giving dataset, and the experimental study is conducted to verify the new data mining method. Experimental
results show that the data mining model based on interval-valued clustering is feasible and effective.