Clustering algorithms are a powerful form of AI that can be applied to business challenges from customer segmentation to fraud detection.

Facility location and clustering algorithms constitute a critical area of research that bridges optimisation theory and data analysis. Facility location techniques focus on the strategic placement ...

In parallel, advances in soft clustering techniques have led to the development of adaptive type2-possibilistic C-means algorithms that address the challenges posed by noise and uncertainty in ...

Economic whiplash like this can be paralyzing. The Federal Reserve’s rate hikes have curbed post-pandemic inflation, but they ...

Then, you can use clustering results to custom tailor your marketing efforts. In this course, we will explore two popular clustering techniques: Agglomerative hierarchical clustering and K-means ...

There are many algorithms available for clustering categorical data. However, the algorithm presented here is relatively simple, has worked well in practice, can be applied to both numeric and ...

Data clustering is the process of placing data items into groups so that items within a group are similar and items in different groups are dissimilar. The most common technique for clustering numeric ...

Statistica Sinica, Vol. 12, No. 1, A Special Issue on Bioinformatics (January 2002), pp. 241-262 (22 pages) Many clustering algorithms have been used to analyze microarray gene expression data. Given ...

Researchers have developed a new tool, bimodularity, that adds directionality to community detection in networks.

The evidence shows that flexible, edge-rich spaces, characterized by modular furniture and intuitive spatial cues, increase ...