NMath Stats

Cluster Analysis, Part IV: Non-negative Matrix Factorization (NMF)

Posted on by Ken Baldwin
In this continuing series, we explore the NMath Stats functions for performing cluster analysis. (For previous posts, see Part 1 - PCA , Part 2 - K-Means, and Part 3 - Hierarchical.) The sample data set we're using classifies 89 single malt scotch whiskies on a five-point scale (0-4) for 12 flavor characteristics. To visualize the data set and clusterings, we make use of the free Microsoft Chart C...
Read More

Clustering Analysis, Part III: Hierarchical Cluster Analysis

Posted on by Ken Baldwin
In this continuing series, we explore the NMath Stats functions for performing cluster analysis. (For previous posts, see Part 1 - PCA and Part 2 - K-Means.) The sample data set we're using classifies 89 single malt scotch whiskies on a five-point scale (0-4) for 12 flavor characteristics. To visualize the data set and clusterings, we make use of the free Microsoft Chart Controls for .NET, which p...
Read More

Clustering Analysis, Part II: K-Means Clustering

Posted on by Ken Baldwin
In this continuing series, we explore the NMath Stats functions for performing cluster analysis in .NET. (For previous posts, see here.) The sample data set we're using classifies 89 single malt scotch whiskies on a five-point scale (0-4) for 12 flavor characteristics. To visualize the data set and clusterings, we make use of the free Microsoft Chart Controls for .NET, which provide a basic set of...
Read More

Clustering Analysis, Part I: Principal Component Analysis (PCA)

Posted on by Ken Baldwin
Cluster analysis or clustering is the assignment of a set of observations into subsets (called clusters) so that observations in the same cluster are similar in some sense. Cluster analysis is the assignment of a set of objects into one or more clusters based on object similarity. NMath Stats includes a variety of techniques for performing cluster analysis, which we will explore in a series of p...
Read More
Top