<prompt> Morero oa ho kopanya lithutong tsa mochini ke ofe?nan  <response>: Instruction in English: What is the purpose of clustering in machine learning? . Response in English: Clustering is a widely used unsupervised machine learning technique that involves grouping together similar data points into clusters based on their characteristics, features, or relationships. The purpose of clustering is to identify underlying patterns, trends and structure in an unlabeled dataset. It is used to discover insights and uncover hidden relationships within the data. Clustering helps to segment data into meaningful groups for further analysis, data compression, and data preprocessing. Clustering is often used for exploratory analysis, customer segmentation, image processing, anomaly detection, and organizing data for easier retrieval and analysis. . Response in Sesotho: Clustering ke mokhoa o sebelisoang haholo oa ho ithuta mochini o sa laoleheng o kenyelletsang ho bokella lintlha tse tšoanang tsa data ka lihlopha ho ipapisitse le litšobotsi tsa bona, likarolo kapa likamano. Sepheo sa ho kopanya ke ho tsebahatsa mekhoa, litloaelo le sebopeho ho datha e sa ngolisoang. E sebelisoa ho fumana lintlha le ho senola likamano tse patiloeng ka hara data. Clustering e thusa ho arola lintlha ka lihlopha tse nang le moelelo bakeng sa tlhahlobo e tsoelang pele, khatello ea data le tsebetso ea data esale pele. Hangata Clustering e sebelisoa bakeng sa tlhahlobo ea lipatlisiso, karohano ea bareki, ho sebetsana le litšoantšo, ho lemoha ka mokhoa o sa tloaelehang, le ho hlophisa lintlha bakeng sa ho fumana le ho hlahloba habonolo. 