Investigating the data-dependent similarity measures for distance-based learning algorithms. The source code of the latest data-dependent similarity measure **aNNE** (AAAI-19) can be obtained from **[here](https://github.com/zhuye88/anne-dbscan-demo)**.
We identify shortcomings of using a tree method to implement Isolation Similarity; and propose a nearest neighbour method instead.
We propose to use mass-based dissimilarity, which employs estimates of the probability mass to measure dissimilarity, to replace the distance metric.
A generic data dependent dissimilarity, named massbased dissimilarity, is proposed to allow for different implementations.