<prompt> Hlalosa bothata boo algorithm ena e bo rarollang.Random Forest  <response>: Instruction in English: Describe the problem that this algorithm solves. . Response in English: Random Forest is a machine learning algorithm that is commonly used for classification and regression tasks. It solves the problem of overfitting, which is when a model is so complex that it fits the training data very well but fails to generalize to new, unseen data. The Random Forest algorithm works by creating multiple decision trees hence the name, forest and then averaging their predictions. By doing this, the model reduces the variance and improves the accuracy and robustness of the prediction. The Random Forest algorithm can also solve the problem of dealing with high dimensional and large datasets, as it is able to select the most important features and build robust models. . Response in Sesotho: Random Forest ke algorithm ea ho ithuta ka mochini e atisang ho sebelisoa bakeng sa ho hlophisa le ho fokotsa mesebetsi. E rarolla bothata ba ho fetela holimo, e leng ha mohlala o rarahane hoo o lumellanang le lintlha tsa koetliso hantle empa o hlōleha ho akaretsa lintlha tse ncha, tse sa bonahaleng. Algorithm ea Random Forest e sebetsa ka ho theha lifate tse ngata tsa liqeto ka hona lebitso, moru ebe e lekanya likhakanyo tsa tsona. Ka ho etsa sena, mohlala o fokotsa phapang mme o ntlafatsa ho nepahala le ho tiea ha ponelopele. Random Forest algorithm e ka boela ea rarolla bothata ba ho sebetsana le li-dataset tse phahameng le tse kholo, kaha e khona ho khetha likarolo tsa bohlokoa ka ho fetisisa le ho haha mehlala e matla. 