Physical Sciences and Mathematics Commons^™

Cluster Analysis Of Mixed-Mode Data, Yawei Liang

Theses and Dissertations

In the modern world, data have become increasingly more complex and often contain different types of features. Two very common types of features are continuous and discrete variables. Clustering mixed-mode data, which include both continuous and discrete variables, can be done in various ways. Furthermore, a continuous variable can take any value between its minimum and maximum. Types of continuous vari- ables include bounded or unbounded normal variables, uniform variables, circular variables, etc. Discrete variables include types other than continuous variables, such as binary variables, categorical (nominal) variables, Poisson variables, etc. Difficulties in clustering mixed-mode data include handling the association …