  A recently proposed clustering method, called the Nearest Descent (ND), can
organize the whole dataset into a sparsely connected graph, called the In-tree.
This ND-based Intree structure proves able to reveal the clustering structure
underlying the dataset, except one imperfect place, that is, there are some
undesired edges in this In-tree which require to be removed. Here, we propose
an effective way to automatically remove the undesired edges in In-tree via an
effective combination of the In-tree structure with affinity propagation (AP).
The key for the combination is to add edges between the reachable nodes in
In-tree before using AP to remove the undesired edges. The experiments on both
synthetic and real datasets demonstrate the effectiveness of the proposed
method.
