Unsupervised Learning in SAS Visual Data Mining and Machine Learning

In a previous post I summarized the tasks and procedures available in SAS Viya Data Mining and Machine Learning. In this post, I'll dive into the unsupervised learning category which currently hosts several tasks: Kmeans, Kmodes, and Kprototypes Clustering, Outlier Detection, and a few variants of Principal Component Analysis. In unsupervised learning there are no known labels (outcomes), only attributes (inputs). Examples include clustering, association, and segmentation. Machine learning finds high density areas (in multidimensional space) that are more or less similar to each other, and identifies structures in the data that separate these areas.