The k-means algorithm is an iterative data clustering algorithm developed by Stuart Lloyd of Bell Labs in the 1950s as a technique for pulse-code modulation. The main idea of the algorithm is that at ...

In this part, you will use the K-means algorithm to select the 16 colors that will be used to represent the compressed image. Concretely, you will treat every pixel in the original image as a data ...

Clustering algorithms are most probably and widely used analysis method for grouping agricultural data with high similarity. For example, one of the most widely used approaches in previous study is ...

The core of WiMi's Trimmed K-Means algorithm is the symmetry and asymmetry of the blockchain. Symmetry, which means that a complete record of transactions is kept at each node, ensures ...

The k-means algorithm is often used in clustering applications but its usage requires a complete data matrix. Missing data, however, are common in many applications. Mainstream approaches to ...