Equal-frequency Interval Binning

Global Algorithm - One-Dimensional Algorithm

Equal-frequency Interval Binning algorithm partitions the data values into disjoint subsets, which have the same number of data samples. The original data are then summarized in each pre-defined subset.

Input Parameters

Parameter	Type	Constraint	Description	Remarks
$Y$	$Y \in \mathbb R^N$	$N \in \mathbb{N}$	Input data vector of length $N$
$n$	$n \in \mathbb N$

Output Parameters

Parameter	Type	Constraint	Description	Remarks
$\hat{Y}$	$\hat{Y} \in \mathbb R^M$	$M \in \mathbb{N}, \quad M \lt N$	Output data vector of length $M$

Single Steps using the Algorithm

• Data Discretization with Equal-frequency Interval Binning
• Data Reduction With Equal-frequency Interval Binning

References

• J. Han, M. Kamber and J. Pei, Data Mining - Concepts and Techniques, 3rd ed., Amsterdam: Morgan Kaufmann Publishers, 2012.