IEEE

Latin Hypercube Sampling Approach to Improve K-Nearest Neighbors Performance on Imbalanced Data

Abstract: Imbalanced class is a common issue encountered in real-world datasets. Oversampling is a technique used to tackle imbalanced classes, with the Synthetic Minority Oversampling Technique ...
GitHub

This project is about implementing Park's (1994) algorithm for Optimal Latin Hypercube sampling in a python function.

This project is not actively worked on right now (May 2023). Until now only the two steps of the first stage of Park's algorithm are implemented. To Dos: Cleaning up the code, modularization More ...
Scientific Research Publishing

Novák, D., Teply, B. and Kersner, Z. (1998) The Role of Latin Hypercube Sampling Method in Reliability Engineering. In: Proc. of ICOSSAR—97, Kyoto, Japan, 403-409.

ABSTRACT: The aim of the paper is to present a newly developed approach for reliability-based design optimization. It is based on double loop framework where the outer loop of algorithm covers the ...
GitHub

latin-hypercube-sampling

Add a description, image, and links to the latin-hypercube-sampling topic page so that developers can more easily learn about it.
Scientific Research Publishing

Gomero, B. (2012) Latin Hypercube Sampling and Partial Rank Correlation Coefficient Analysis Applied to an Optimal Control Problem. Master’s Thesis, University of Tennessee ...

ABSTRACT: In this paper, we are interested to find the most sensitive parameter, local and global stability of ovarian tumor growth model. For sensitivity analysis, we use Latin Hypercube Sampling ...