Research Article
K-Mean Clustering
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 177 - Issue 47 |
| Published: Mar 2020 |
| Authors: Xi Chen |
10.5120/ijca2020919937
|
Xi Chen . K-Mean Clustering. International Journal of Computer Applications. 177, 47 (Mar 2020), 24-27. DOI=10.5120/ijca2020919937
@article{ 10.5120/ijca2020919937,
author = { Xi Chen },
title = { K-Mean Clustering },
journal = { International Journal of Computer Applications },
year = { 2020 },
volume = { 177 },
number = { 47 },
pages = { 24-27 },
doi = { 10.5120/ijca2020919937 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2020
%A Xi Chen
%T K-Mean Clustering%T
%J International Journal of Computer Applications
%V 177
%N 47
%P 24-27
%R 10.5120/ijca2020919937
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In this paper, I apply K-mean clustering method to test the validity of Bank notes by separating notes in the real or fake group automatically with Python 3 in the Jupyter Lab.
References
- Khan, Muhammad Rizwan. “K Means Clustering Algorithm & Its Application.” Medium, Data Driven Investor, 12 Oct. 2018, https://medium.com/datadriveninvestor/k-means-clustering-algorithm-its-application-ff9e97297e6e.
- “k-Means Advantages and Disadvantages | Clustering in Machine Learning.” Google, Google, https://developers.google.com/machinelearning/clustering/algorithm/advantages-disadvantages.
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