Research & Development

December 12, 2017

Working with High-Dimensional Data Part 4: Classifying Unknown Samples using Machine Learning Principles

In the previous articles in this series (part 1, part 2, and part 3) we’ve been performing analyses on an example high-dimensional […]
December 5, 2017

Working with High-Dimensional Data Part 3: Geospatial Mapping and Mine Planning

  In part 1 of this introductory series about working with high-dimensional data we looked at dimensionality reduction to allow the visualisation […]
November 14, 2017

Working with High-Dimensional Data, Part 1: Dimensionality Reduction

Mineral exploration, mining, ore processing, and, more generally, earth science research, involves the collection of large and complex data sets where single […]
August 2, 2017

THE IMPORTANCE OF MINERAL DEFINITIONS USED IN GENERATING QEMSCAN DATA

The most common approach to assessing the accuracy of QEMSCAN mineralogy results is to compare the measured assay with the mineralogy-computed chemical […]
July 26, 2017

Three areas that may affect the quality of your mineralogy data

  The complex nature of QEMSCAN mineralogy results necessitates a thorough assessment of data quality relative to ‘best practices’ values. The MinAssist […]
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