Dissimilarity of Observations for Sparse Numerical Data
How to measure the dissimilarity of observations for sparse numerical data – a novel approach using weighted symmetric and asymmetric binary distances.
Distance Between Observations (Numeric & Ordinal Data)
In order to “cluster” observations we need some measure of how alike or different they are. This leads naturally to the concept of a distance between observations. Here we explore how to calculate the distance between observations made up of numerical and ordinal data.
Cluster Analysis – How to Find Categories in Data
The problem of categorization presents itself in many aspects of life. When marketers talk of “market segmentation” they essentially mean: “what categories of customer are there?” When investors talk of “asset classes” they...Ian Rayner
Hedge fund advisor: Make smarter allocations. Build better portfolios.