2.3. Clustering
2.3. Clustering
Clustering of unlabeled data can be performed with the module sklearn.cluster.
Each clustering algorithm comes in two variants: a class, that implements the fit method to learn the clusters on train data, and a function, that, given train data, returns an array of integer labels corresponding to the different clusters. For the class, the labels over the training data can be found in the labels_ attribute.
Input data
One important thing to note is that the algorithms implemented in this module can take different kinds of matrix as input. All the methods accept standard data ma
