<prompt> Hlalosa hore na algorithm e latelang ea ho ithuta mochini e etsa eng.K-Ho Bolela ho Kopanya  <response>: Instruction in English: Explain what the following machine learning algorithm does. . Response in English: K-Means Clustering is an unsupervised machine learning algorithm used to identify and separate data into groups based on similarities or patterns within the data. The algorithm works by defining a specified number of clusters, K, and assigns each data point to one of these clusters based on its distance to the center of the cluster, also known as the centroid. The algorithm then iteratively updates the cluster assignments by minimizing the sum of the squared distances between each data point and its assigned clusters centroid.During the process, the algorithm constantly recalculates the position of the centroid, leading to a reassignment of data points to clusters, until it finally converges to an optimal solution. The end result is a set of clearly defined clusters, each containing a group of data points that are most similar to one another.K-Means Clustering is a popular algorithm used in areas such as market segmentation, image segmentation, and anomaly detection. It is also commonly used as a preprocessing step for other machine learning algorithms to make their input data more organized and easier to process. . Response in Sesotho: K-Means Clustering ke mokhoa o sa laoleheng oa ho ithuta oa mochini o sebelisetsoang ho khetholla le ho arola lintlha ka lihlopha ho ipapisitse le ho tšoana kapa lipaterone ka hara data. Algorithm e sebetsa ka ho hlalosa palo e itseng ea lihlopha, K, me e abela ntlha ka ngoe ea data ho e ngoe ea lihlopha tsena ho ipapisitsoe le sebaka sa eona sa bohareng ba sehlopha, se tsejoang hape e le centroid. Joale algorithm e nchafatsa likabelo tsa sehlopha ka ho fokotsa kakaretso ea sebaka se sekwere lipakeng tsa ntlha e ngoe le e ngoe ea data le centroid ea sehlopha seo e se abetsoeng. Nakong ea tsebetso, algorithm e lula e lekola boemo ba centroid, e lebisang ho arolelanoeng lintlha tsa data ho lihlopha, ho fihlela qetellong e fetoha tharollo e nepahetseng. Sephetho ke sehlopha sa lihlopha tse hlalositsoeng ka ho hlaka, se seng le se seng se na le sehlopha sa lintlha tsa data tse tšoanang haholo. K-Means Clustering ke algorithm e tsebahalang e sebelisoang libakeng tse kang karohano ea maraka, karohano ea litšoantšo, le ho lemoha ka mokhoa o sa tloaelehang. E boetse e sebelisoa ka tloaelo e le mohato oa ho lokisa pele bakeng sa li-algorithms tse ling tsa ho ithuta mochini ho etsa hore data ea bona e kenngoeng e hlophisehe le ho e sebetsa habonolo. 