The Explore tab provides access to Dimensionality Reduction via Feature Selection, and the ability to explore data using charts such as Bar Charts, Line Charts, Scatterplots, Boxplots, Histograms, Parallel Coordinates, ScatterPlot Matrices, and Variable Plots.

Dimensionality Reduction is the process of deriving a lower-dimensional representation of original data, which still captures the most significant relationships to be used to represent the original data in a model.  This domain can be divided into two branches, feature selection and feature extraction. Feature Selection attempts to discover a subset of the original variables, while Feature Extraction attempts to map a high-dimensional model to a lower-dimensional space. In past versions, XLMiner contained one feature extraction tool that could be used outside of a classification or prediction method, Principal Components Analysis (Transform – Principal Components on the XLMiner ribbon); however, in V2015, Feature Selection was added.