Homogeneous bipartition based on multidimensional ranking

We present an algorithm which partitions a data set in two parts with equal size and experimentally nearly the same distribution measured through the likelihood of a Parzen kernel density estimator. The generation of the partition takes O(1 2 N(N - 1)) operations (N number of data) and is 2 orders of magnitude faster than the state of the art. 1 Generating an equi-distributed bipartition

• Type: Conference
• Year: 2008
• Where: ESANN
• Authors: Michaël Aupetit
• Keywords: Data Set, Equal Size, ESANN 2008, Neural Networks, Parzen Kernel Density