<prompt> Ke karolo efe thutong ea mochini e hlokometsoeng?nan  <response>: Instruction in English: What is a feature in supervised machine learning? . Response in English: A feature in supervised machine learning refers to a measurable characteristic or attribute of a data sample which is used as an input variable for creating a predictive model. It is also commonly referred to as a predictor variable, independent variable or input variable. Features play a critical role in machine learning as they act as the variables that help the model learn to accurately predict the targeted outcome. In supervised learning, the selection and engineering of the right features in the dataset is an essential step in developing a high-performing predictive model, as the quality and relevance of the input features will greatly impact the models overall accuracy. . Response in Sesotho: Karolo e itseng thutong ea mochini e hlokometsoeng e bua ka tšobotsi e lekantsoeng ea sampole ea data e sebelisoang e le mokhoa oa ho kenya letsoho bakeng sa ho etsa mofuta o lekanyelitsoeng. E boetse e bitsoa predior variable, ipeo e ikemetseng kapa input variable. Likarolo li bapala karolo ea bohlokoa thutong ea mochini ha li ntse li sebetsa joalo ka mefuta e thusang mohlala ho ithuta ho bolela esale pele sephetho se reriloeng. Thutong e hlokometsoeng, khetho le boenjineri ba likarolo tse nepahetseng pokellong ea data ke mohato oa bohlokoa oa ho theha mohlala oa ponelopele o sebetsang hantle, kaha boleng le bohlokoa ba likarolo tsa ho kenya li tla ama haholo ho nepahala ha kakaretso ea mohlala. 