RPTree

The Effect of Points Dispersion on the k-nn Search in Random Projection Forests

This is an implementation for our paper in IEEE Access:

@ARTICLE{9846977,
	author	  = {Alshammari, Mashaan and Stavrakakis, John and Ahmed, Adel F. and Takatsuka, Masahiro},
	journal	  = {IEEE Access}, 
	title	  = {The Effect of Points Dispersion on the k-nn Search in Random Projection Forests}, 
	year 	  = {2022},
	volume	  = {10},
	pages	  = {80858-80868},
	doi	  = {10.1109/ACCESS.2022.3195488}}

How to use:

RPTree.py

this python file contains the BinaryTree class, which performs the following tasks:

• construct_tree
• get_leaf_nodes
• preorder_search

RunMain.py

this python file contains the driver code to create BinaryTree instance, then performs the following tasks:

• picks a random test sample, and removes it from the dataset.
• creates the rpTree from the dataset.
• performs k-nn search on the rpTree to find the nearest neighbors for the test sample.