A von Mises-Fisher mixture model for clustering numerical and categorical variables. (English) Zbl 07597423
Summary: This work presents a mixture model allowing to cluster variables of different types. All variables being measured on the same \(n\) statistical units, we first represent every variable with a unit-norm operator in \({\mathbb{R}}^{n\times n}\) endowed with an appropriate inner product. We propose a von Mises-Fisher mixture model on the unit-sphere containing these operators. The parameters of the mixture model are estimated with an EM algorithm, combined with a K-means procedure to obtain a good starting point. The method is tested on simulated data and eventually applied to wine data.
MSC:
| 62H11 | Directional data; spatial statistics |
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