<prompt> Ka kopo fana ka mohlala oa tlhahiso bakeng sa mosebetsi oa ho hlophisa.nan  <response>: Instruction in English: Please provide a sample input for a classification task. . Response in English: A sample input for a classification task would be a dataset with multiple instances observations and their corresponding features and label class. The features are the independent variables used to predict the label, which is the dependent variable.For example, a dataset for a binary classification task to predict whether a person has diabetes or not could have the following input: Age Gender BMI BloodPressure Glucose Diabetes --- --- --- --- --- --- 45 F 25.3 80 95 No 63 M 32.2 94 168 Yes 35 F 19.3 70 85 No 52 M 27.8 87 115 No 57 F 34.2 92 155 Yes In this case, the features are: Age, Gender, BMI, BloodPressure, and Glucose while the label is Diabetes with two possible classescategorical variable: Yes or No. . Response in Sesotho: Mohlala oa tlhahiso bakeng sa mosebetsi oa ho hlophisa e ka ba pokello ea data e nang le maemo a mangata litebello le likarolo tsa tsona tse tsamaellanang le leibole sehlopha. Likarolo ke mefuta e ikemetseng e sebelisoang ho bolela esale pele label, e leng mofuta o itšetlehileng ka oona. Ka mohlala, dataset bakeng sa mosebetsi oa binary classification ho bolela esale pele hore na motho o na le lefu la tsoekere kapa che e ka ba le lintlha tse latelang: Lilemo Bong BMI Khatello ea Mali Glucose Lefu la tsoekere --- --- --- --- --- --- 45 F 25.3 80 95 Che 63 M 32.2 94 168 Ho joalo 35 F 19.3 70 85 Che 52 M 27.8 87 115 Che 57 F 34.2 92 155 Ho joalo Tabeng ena, likarolo ke tsena: Lilemo, Tekano, BMI, BloodPressure, le Glucose ha leibole e le Lefu la tsoekere le nang le lihlopha tse peli tse ka khonehang mefuta e fapaneng ea lihlopha: E kapa Che. 