A more efficient algorithm to compute the Rand Index for change-point problems

12/07/2021
by   Lucas de Oliveira Prates, et al.
0

In this paper we provide a more efficient algorithm to compute the Rand Index when the data cluster comes from change-point detection problems. Given N data points and two clusters of size r and s, the algorithm runs on O(r+s) time complexity and O(1) memory complexity. The traditional algorithm, in contrast, runs on O(rs+N) time complexity and O(rs) memory complexity.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/12/2019

An Efficient Skyline Computation Framework

Skyline computation aims at looking for the set of tuples that are not w...
research
02/17/2017

Objective Bayesian Analysis for Change Point Problems

In this paper we present an objective approach to change point analysis....
research
11/17/2020

Adjusting the adjusted Rand Index – A multinomial story

The Adjusted Rand Index (ARI) is arguably one of the most popular measur...
research
05/26/2017

An Efficient Algorithm for Bayesian Nearest Neighbours

K-Nearest Neighbours (k-NN) is a popular classification and regression a...
research
04/29/2018

A linear time algorithm for multiscale quantile simulation

Change-point problems have appeared in a great many applications for exa...
research
12/10/2019

A Fast Self-correcting π Algorithm

We have rediscovered a simple algorithm to compute the mathematical cons...
research
12/24/2021

Dimensional Complexity and Algorithmic Efficiency

This paper uses the concept of algorithmic efficiency to present a unifi...

Please sign up or login with your details

Forgot password? Click here to reset