Clustering is an unsupervised machine learning method that is used for splitting the original dataset of objects into groups classified by properties. An object in machine learning is usually treated as a point in the multidimensional metric space. Every space dimension corresponds to an object property (feature), and the metric is a function of the values of these properties. Depending on the types of dimensions in this space, which can be both numerical and categorical, we choose the type of clustering algorithm and specific metric function. This choice depends on the nature of different object properties' types.
The main difference between clustering and classification is an undefined set of target groups, which is determined by the clustering algorithm. The set of target groups (clusters) is the algorithm's result.
We can split cluster analysis into the...
