Cluster analysis or clustering is the task of partitioning a set of objects into groups called clusters, with the goal of grouping similar objects into the same cluster. It is a main tool of exploratory data mining, and a common technique for statistical data analysis, used in many fields, including machine learning, pattern recognition, image analysis, information retrieval, and bioinformatics. In this demo we generate a group of data points and feed them to the k-means clustering algorithm that classifies them into a given number of clusters.

• Demo Code
• K-means Input
• K-means Output

Algorithmia.client(api_key).algo("/kenny/WekaCluster").pipe([
  dataPoints,
  numClusters
]).then(console.log);