Exploring data by PCA and k-means for IEEE Xplore digital library
John Anzola, Luz Andrea Rodríguez, Giovanny Mauricio Tarazona Bermúdez · 2016
An important feature in data analysis is the exploration and data representation. This article describes the Principal Components Analysis techniques (PCA) and clusters analysis with k-means, in order to represent a set of two-dimensional spatial data and group similar data to find relationships between the two techniques. Data is extracted from IEEE Xplore digital library, which lacks processing tools and information display since it doesn't permit analysis and identification of trends and patterns in a query.