R Advanced: Data Clustering and Segmentation Analysis

Ironfrown's ...to be or not to be for those who R... a video series on advanced topics in R. This one on clustering, robust methods and deployment! This video describes the concept of data clustering, explains its aims, data preparation for cluster analysis, visualization techniques for cluster diagnostics and for segmentation analysis, as well as cluster optimization methods. The presentation focuses on business applications of data clustering for R practitioners. Because of this we set two key objectives. The first objective is to utilize robust methods that are not sensitive to outliers. The second aim is to create an analytic process that could be deployed and applied to new data. Sources on GitHub: * https://github.com/ironfrown/r-examples Data prepared by: Dean De Cock, "Ames, Iowa: Alternative to the Boston Housing Data as an End of Semester Regression Project", Journal of Statistics Education, Volume 19, Number 3(2011). Source of the original data and its description: * http://jse.amstat.org/v19n3/decock/AmesHousing.txt * http://jse.amstat.org/v19n3/decock/DataDocumentation.txt Also available on Kaggle: * https://www.kaggle.com/prevek18/ames-housing-dataset Videos by ironfrown.