Suppose you have been building a model using the K-means clustering algorithm and you keep finding that a certain variable is essentially ignored by the model. And from your work in selecting variables for a model, you probably implicitly developed 'rules of thumb' to determine which variable should be considered for the model and which ones could be ignored. Please summarize your own criteria that outlines how you determine relevant variables that significantly influence the phenomenon under investigation.