krms 0.0.2

# krms

A simple python library for implementing the K-RMS Clustering algorithm on unlabelled data using unsupervised learning.

The code is Python 2 and 3 compatible.

# Installation

Fast install:

pip install krms

For a manual install get this package:

$wget https://github.com/garain/krms/archive/master.zip
$unzip master.zip
$rm master.zip
$cd krms-master

Install the package:

python setup.py install

# Example

from krms import krms_clustering

#For results related to Iris dataset no need to pass any argument.
krms_clustering.run()

#For getting results from custom dataset pass path of csv file as argument in function 'run'.
krms_clustering.run("data.csv")

N.B.: The csv file should have the labels in first column with header name ‘type’ followed by rest of feature columns.

# References

@article{GARAIN2020113,
title = "K-RMS Algorithm",
                journal = "Procedia Computer Science",
                volume = "167",
                pages = "113 - 120",
                year = "2020",
                note = "International Conference on Computational Intelligence and Data Science",
                issn = "1877-0509",
                doi = "https://doi.org/10.1016/j.procs.2020.03.188",
                url = "http://www.sciencedirect.com/science/article/pii/S1877050920306530",
                author = "Avishek Garain and Dipankar Das",
                keywords = "clustering, distortion-error, rms-value, multi-component analysis, unsupervised-learning"
                }