<prompt> Bala phoso ea root-mean-square me u hlalose hore na e lekanya eng.nan  <response>: Instruction in English: Calculate the root-mean-square error and explain what it measures. . Response in English: The root-mean-square error RMSE is a measure of how well a model is able to predict values. It measures the average magnitude of the errors in the set of predictions, providing an idea of the overall accuracy of the model.To calculate RMSE, we first calculate the difference between the predicted and actual values for each observation. Then, we square the residuals, sum them and take the average. You can do this by dividing the summed squared errors by the number of observations. Finally, we take the square root of the average, resulting in the RMSE. The formula to compute the RMSE is: RMSE sqrtsumy_pred - y_actual2 nWhere:- y_pred is the predicted value.- y_actual is the actual, observed value.- n is the number of observations.RMSE is a useful measure when evaluating a models performance for continuous data. It depicts in the same unit scale as the response variable. Low RMSE values indicate a better model fit, and a value of 0 means that the model perfectly predicts all the observations. . Response in Sesotho: The root-mean-square error RMSE ke tekanyo ea hore na mohlala o khona ho lepa litekanyetso hantle hakae. E lekanya boholo ba karolelano ea liphoso sehlopheng sa likhakanyo, e fana ka maikutlo a ho nepahala ha kakaretso ea mohlala. Ho bala RMSE, re qala ka ho bala phapang lipakeng tsa litekanyetso tse boletsoeng esale pele le tsa nete bakeng sa tlhokomeliso ka ngoe. Ebe, re sekoere masala, re a akaretsa ebe re nka karolelano. U ka etsa sena ka ho arola liphoso tse akaretsang tsa squared ka palo ea litebello. Qetellong, re nka square root ea karolelano, e hlahisang RMSE. Mokhoa oa ho kopanya RMSE ke: RMSE sqrtkakaretsoy_pred - y_actual2 n Moo: - y_pred ke boleng bo boletsoeng esale pele. - y_ea sebele ke boleng ba sebele, bo hlokometsoeng. - n ke palo ea litebello. RMSE ke mohato o molemo ha o hlahloba tsebetso ea mohlala bakeng sa data e tsoelang pele. E tšoantšetsa ka tekanyo ea yuniti e tšoanang le phapang ea karabo. Maemo a tlase a RMSE a bontsa mofuta o betere, me boleng ba 0 bo bolela hore mohlala o bolela esale pele litebello tsohle. 