Equal-frequency Interval BinningΒΆ

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 \(N\) None
\(n\) \(n \in \mathbb N\) None None None

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 \(M\) None

Single Steps using the Algorithm

References

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