In my project, I am facing a multi-class classification problem.
As a first research/modeling step, I used a clustering algorithm with 3 clusters.
Motivation behind this step, was to understand potential patterns in the feature space. And their relation to the class variable(y).
Clustering results showed, there is an equal distribution of the 3 target classes values in each of the clusters.
My question is: do the 'similar' distribution of target variable on the 3 clusters suggest that classification task would be difficult based on existing features?
When clustering with more than 3 clusters I got similar results.
My dataset has 150 features and ok 20 000 instances.