Dear Md. Ektear Uddin

These links might be useful, have a look:

1. https://stats.stackexchange.com/questions/40613/why-dont-dummy-variables-have-the-continuous-adjacent-category-problem-in-clust

2. https://datascience.stackexchange.com/questions/22/k-means-clustering-for-mixed-numeric-and-categorical-data

3. https://www.ibm.com/support/pages/clustering-binary-data-k-means-should-be-avoided

Kind Regards

Qamar Ul Islam

There are some problem where we cannot apply ML algorithms. Similarly, it is inappropriate to apply KNN like clustering algorithm on 'Yes/No' nominal data. I feel the direct application of clustering algorithm on this data will not give results. If anything relevant, kindly update. But, your logic is correct.

Hi. I hope the following link might help:

https://towardsdatascience.com/clustering-datasets-having-both-numerical-and-categorical-variables-ed91cdca0677?gi=192501566055

Can. To do this, you first need to metrize the nominal scales.

https://www.researchgate.net/publication/331801337

For example, as in the Eidos system: http://lc.kubagro.ru/aidos/The_Eidos_en.htm

Check https://www.researchgate.net/publication/228758935_Cluster_analysis_and_categorical_data

Also check https://www.statisticssolutions.com/free-resources/directory-of-statistical-analyses/cluster-analysis/

Also check this

Article Cluster analysis and categorical data