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 ...

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 ...

K-Means Clustering An unsupervised learning algorithm, k-means clustering takes datasets with certain features and values related to these features and groups data points into a number of clusters.

Entropy Minimization is a new clustering algorithm that works with both categorical and numeric data, and scales well to extremely large data sets.

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 ...

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 ...