Sunday, 22 May 2011

k-means clustering

The F#.NET Journal just published an article about machine learning:

"The k-means clustering algorithm is a simple form of machine learning that categorizes a set of data points into k clusters each centered around its own centroid. This article describes the design and implementation of the k-means clustering algorithm and an example application to a standard Iris flower data set including downloading and massaging the data directly from the web and visualizing the resulting clusters using WPF and the new charting and graphing functionality in .NET 4..."

To read this article and more, subscribe to The F#.NET Journal today!

Saturday, 7 May 2011

Allocationless programming on .NET

The F#.NET Journal just published another article about low-latency programming:

"An extreme technique used in some latency-critical applications is to completely circumvent the garbage collector by replacing all heap allocations with the use of pre-allocated arrays of value types, effectively implementing manual memory management inside a managed programming language. This might be called Fortran-style programming on .NET but the advantage is that stalls due to garbage collection can be made less frequent or even eliminated entirely..."

To read this article and more, subscribe to The F#.NET Journal today!