I have a large labeled dataset with 29 classes. Is is possible to use a clustering algorithm (like k-means) in this dataset, or it's not possible since clustering algorithms are unsupervised ?
You can do many things:
- Forget about the labels: just use the features that are not labels and cluster along those features using the k-means algorithm (or another).
- Forget about the features: this is the dummiest way of clustering. Cluster the data in 29 clusters according to the labels that they have. If you want less clusters, you can compute the centroids of the classes and use them to join clusters of different labels.
- Use everything: create a categorical variable refering to the class that every example belongs to. Then, with this new variable and all the features perform a classical clustering algorithm.
The way to proceed depends on if you want to use the labels or not, and how much importance you want them to have.