# Clustering

The clustering, which is the unsupervised grouping task of unlabelled data, can be carried out using the following methods:

- Agglomerative
- KMeans

Attention: Available only with Activate commercial edition.

The clustering, which is the unsupervised grouping task of unlabelled data, can be carried out using the following methods:

- Agglomerative
- KMeans

**agglomerativefit**

Agglomerative clustering. It is an unsupervised learning algorithm. It recursively merges the pair of clusters that minimally increase a given linkage distance.**agglomerativepredict**

Predicts target values for the test data points using parameters computed by agglomerativeFit function. In agglomerative clustering, again fitting is done with the given test data points and the options set during training. So instead can use the labels of the output of fit method.**kmeansfit**

K-Means clustering. It's an unsupervised learning algorithm.**kmeanspredict**

Predicts target values for the test data points using parameters computed by kmeansFit function.