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}}
this python file contains the BinaryTree
class, which performs the following tasks:
construct_tree
get_leaf_nodes
preorder_search
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.