# Equal-frequency Interval Binning¶

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

References

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