<prompt> Theha pokello ea lintlha bakeng sa mosebetsi oa ho hlophisa.nan  <response>: Instruction in English: Create a dataset for a classification task. . Response in English: Here is a sample dataset for a binary classification task: Feature 1 Feature 2 Feature 3 Feature 4 Label--- --- --- --- --- 1.1 3.5 0.3 9 0 0.2 1.6 2.2 5 1 0.7 2.5 1.3 8 0 0.4 4.5 1.7 6 1 1.2 2.4 0.5 7 0 1.5 1.4 2.2 4 1 2.2 3.1 1.5 3 1 0.3 3.3 1.1 2 0 - In this dataset, there are 4 input features Feature 1, Feature 2, Feature 3 and Feature 4 and a binary label 0 or 1 representing the class of each instance.- The features can represent any characteristic of the data, such as attributes of an item or measurements taken in an experiment.- The label represents the class assigned to each data point, this can represent two different outcomes or conditions of the data.- This dataset can be used to train a machine learning model to learn and predict the class of new data points based on their features. . Response in Sesotho: Mona ke mohlala oa datha bakeng sa mosebetsi oa ho arola li binary: Sebopeho sa 1 Sebopeho sa 2 Feature 3 Tlhahiso ea 4 Label --- --- --- --- --- 1.1 3.5 0.3 9 0 0.2 1.6 2.2 5 1 0.7 2.5 1.3 8 0 0.4 4.5 1.7 6 1 1.2 2.4 0.5 7 0 1.5 1.4 2.2 4 1 2.2 3.1 1.5 3 1 0.3 3.3 1.1 2 0 - Lethathamong lena la boitsebiso, ho na le likarolo tse 4 tsa ho kenya Tlhahiso ea 1, Karolo ea 2, Karolo ea 3 le ea 4 le laibole ea binary 0 kapa 1 e emelang sehlopha sa ketsahalo ka ngoe. - Likarolo li ka emela tšobotsi efe kapa efe ea data, joalo ka litšoaneleho tsa ntho kapa litekanyo tse nkuoeng tekong. - Leibole e emela sehlopha se abetsoeng ntlha ka ngoe ea data, sena se ka emela liphetho tse peli tse fapaneng kapa maemo a data. - Lethathamo lena la data le ka sebelisoa ho koetlisa mohlala oa ho ithuta mochini ho ithuta le ho bolela esale pele sehlopha sa lintlha tse ncha tsa data ho latela likarolo tsa bona. 