<prompt> Hlalosa Mokhoa oa ho Clustering?nan  <response>: Instruction in English: Describe the Clustering Method? . Response in English: Clustering is a method of grouping objects in such a way that objects in the same group are more similar to each other than to those in other groups, based on a given similarity measure. It is a form of unsupervised learning, meaning that it does not require labeled training data, but instead relies on the structure of the data to discover meaningful subgroups. Clustering can be applied to a wide variety of data types, such as image or text data, and is often used as a pre-processing step for machine learning or data analysis tasks. There are many clustering algorithms available, including k-means, hierarchical clustering, and density-based clustering. These algorithms differ in their approach for determining the number of clusters, the shape of clusters, and the similarity measure used to compare data points. . Response in Sesotho: Ho bokellana ke mokhoa oa ho hlophisa lintho ka tsela eo lintho tse sehlopheng se le seng li tšoanang ka tsona ho feta tse lihlopha tse ling, ho itšetlehile ka tekanyo e fanoeng ea ho tšoana. Ke mofuta oa thuto e sa laoleheng, ho bolelang hore ha e hloke boitsebiso bo ngotsoeng ba koetliso, empa ho e-na le hoo e itšetlehile ka sebopeho sa boitsebiso ho fumana lihlopha tse nyenyane tse nang le moelelo. Ho kopanya ho ka sebelisoa mefuteng e mengata e fapaneng ea data, joalo ka setšoantšo kapa data ea mongolo, me hangata e sebelisoa e le mohato oa pele oa ho sebetsa bakeng sa ho ithuta mochini kapa mesebetsi ea tlhahlobo ea data. Ho na le li-algorithms tse ngata tsa ho kopanya tse fumanehang, ho kenyeletsoa k-means, sehlopha sa maemo a holimo, le lihlopha tse thehiloeng ho bongata. Li-algorithms tsena li fapana ka mokhoa oa tsona oa ho khetholla palo ea lihlopha, sebōpeho sa lihlopha, le tekanyo ea ho tšoana e sebelisoang ho bapisa lintlha tsa data. 