The Difficulties Presented by High-Dimensional Data

A central use of the PolyChord tool is solving problems presented by high-dimensional data. High-dimensional data is constantly analysed in an attempt to create data models and formulas. If an accurate model is produced then the model can be used to create highly accurate future predictions. However, creating a model to fit high-dimensional data is an extremely difficult task.

This article by Sunil Sapra discusses the use of high-dimensional data and is a great explanation of the difficulties that come with fitting a model for high-dimensional data.

Here at PolyChord, we have been able to overcome a majority of these difficulties by using advanced machine learning techniques. Unlike other companies, PolyChord takes an orthogonal approach using nested sampling to navigate thousands of dimensions and compute without compromises or approximation.

****Disclaimer: Dr. Sapra is not associated with the PolyChord organisation****

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