Mixed‐Condorcet: An Advanced Method of Clustering for Mixed Data in Social Sciences

This paper provides a new clustering method for mixed data based on α ‐Condorcet, denoted mixed‐Condorcet, by introducing a new Condorcet criterion. This criterion combines α ‐Condorcet and k ‐prototype criteria. Next, we give the within‐cluster sum‐of‐squares expression for our new method. Furthermore, we compare mixed‐Condorcet clustering with k ‐prototype and Kamila clustering. The comparison employs quality index (QI) and a within cluster sum of squares index. Our findings are illustrated using both simulated and real datasets.