Explorer Challenge28 Feb - 31 May
A $1 Million prize pool on a journey to discovery with data
This competition has finished.
Target selection at Mt Woods. A data dimensionality reduction and clustering approach.
Our approach uses data dimensionality reduction and clustering techniques to compare relationships between element concentrations of analytical results with commodities of interest. Dimensionality reduction is the process of reducing the number of indicator variables (columns in a table) to a set of principal variables, usually two dimensions that can be visualized and interpreted as an X and Y relationship in a plot. Clustering techniques can be applied to the two-dimensional outputs from dimensionality reduction to group, extract, and classify data points.