klusterointimenetelmän
Klusterointimenetelmä, known in English as clustering method, is a fundamental technique in unsupervised machine learning. Its primary goal is to partition a set of data points into groups, or clusters, such that data points within the same cluster are more similar to each other than to those in other clusters. This method does not require pre-labeled data, making it useful for exploratory data analysis and discovering inherent structures within datasets.
Various algorithms exist for performing clustering, each with its own approach to defining similarity and forming
The choice of clustering method often depends on the characteristics of the data and the desired outcome.