Cluster analysis enables investors to eliminate overlap in their portfolio by identifying securities with related returns. For example, a portfolio of only technology stocks may seem safe and ...

Industries from retail to finance are using clustering to personalize services, detect fraud, monitor equipment and improve ...

Example 23.3: Cluster Analysis of Fisher Iris Data The iris data published by Fisher (1936) have been widely used for examples in discriminant analysis and cluster analysis. The sepal length, sepal ...

Cluster analysis tells you about clusters of words that are getting stronger or weaker. For example, it is clear the probability that BP and "oil spill" appear close to each other spiked recently.

it is classified as cluster 7 with 29 misclassifications. In summary, when the standardization method is STD, seven species of fish are classified into only 5 clusters and the total number of ...

The goal of clustering analysis is to establish a set of meaningful groups of similar objects by investigating relationships between objects. For example, if you have data from customers, you may ...

For example, we might want to partition a set ... However, the end user's ability to perform a successful cluster analysis depends on much more than an efficient algorithm. Most important is ...

Cluster analysis yielded four clusters with reasonable overall structure ... pending replication of these findings in a larger, representative sample. This paper also provides guidance for development ...