GitHub

Behrouz-Babaki/COP-Kmeans

usage: run_ckm.py [-h] [--ofile OFILE] [--n_rep N_REP] [--m_iter M_ITER] [--tol TOL] dfile cfile k Run COP-Kmeans algorithm positional arguments: dfile data file cfile constraint file k number of ...
IEEE

K-means Clustering Solution for Image Compression

Abstract: The paper presents a detailed research study of the k-means clustering algorithm to be used for image compression tasks, where the RGB values of the colors are considered XYZ coordinates of ...
Frontiers

Systems Neuroscience Computing in Python (SyNCoPy): a python package for large-scale analysis of electrophysiological data

We introduce an open-source Python package for the analysis of large-scale electrophysiological data, named SyNCoPy, which stands for Systems Neuroscience Computing in Python. The package includes ...
Scientific Research Publishing

Enhancing Data Analysis and Automation: Integrating Python with Microsoft Excel for Non-Programmers ()

Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and ...
Visual Studio Magazine

Clustering Mixed Categorical and Numeric Data Using k-Means with C#

Dr. James McCaffrey of Microsoft Research presents a full-code, step-by-step tutorial on a "very tricky" machine learning technique. Data clustering is the process of grouping data items together so ...
Visual Studio Magazine

DBSCAN Data Clustering from Scratch Using C#

Compared to other clustering techniques, DBSCAN does not require you to explicitly specify how many data clusters to use, explains Dr. James McCaffrey of Microsoft Research in this full-code, ...
Scientific Research Publishing

Maternal and Child Health Care Quality Assessment: An Improved Approach Using K-Means Clustering ()

1 Department of Communication Science and Engineering, Nelson Mandela Institution of Science and Technology, Arusha, Tanzania. 2 School for Information Sciences, Center for Information and Systems, ...
IEEE

K-means clustering algorithm and Python implementation

Abstract: K-means is a commonly used algorithm in machine learning. It is an unsupervised learning algorithm. It is regularly used for data clustering. Only the number of clusters are needed to be ...