<prompt> Haha binary classifier ho khetholla pakeng tsa liapole le lilamunu.Apple: e khubelu, e chitja, tart Orange: lamunu, le chitja, le monate  <response>: Instruction in English: Build a binary classifier to differentiate between apples and oranges. . Response in English: For building a binary classifier that differentiates between apples and oranges based on given input, one possible approach with an example in Python could be:pythonfrom sklearn.tree import DecisionTreeClassifierfrom sklearn import preprocessingcolor red, orangeshape round, roundflavor tart, sweet encoding string labels into numeric le preprocessing.LabelEncodercolor_encoded le.fit_transformcolor 0, 1shape_encoded le.fit_transformshape 0, 0flavor_encoded le.fit_transformflavor 1, 0features listzipcolor_encoded, shape_encoded, flavor_encoded 0, 0, 1, 1, 0, 0 labels 0:apple, 1:orangelabels 0, 1 clf DecisionTreeClassifierclf clf.fitfeatures, labels Predicting the class color: red0, shape: round 0, flavor: tart 1prediction clf.predict0, 0, 1printprediction 0 : apple Predicting the class color: orange1, shape: round 0, flavor: sweet 0prediction clf.predict1, 0, 0printprediction 1 : orangeHere, we used a decision tree classifier that utilizes given input features to differentiate between apple and orange. The input features are encoded in numeric values, and then used with labels to train the model. Then, the model can be used for predictions. . Response in Sesotho: Bakeng sa ho aha binary classifier e khethollang lipakeng tsa liapole le lilamunu ho ipapisitsoe le kenyeletso e fanoeng, mokhoa o le mong o ka sebelisoang ka mohlala ho Python e ka ba: python from sklearn.tree import DecisionTreeClassifier from sklearn import preprocessing color red, orange sebopeho pota, chitja flavor tart, sweet lileibole tsa khoele tsa khoele ka linomoro le preprocessing.LabelEncoder color_encoded le.fit_transformcolor 0, 1 shape_encoded le.fit_transformshape 0, 0 flavor_encoded le.fit_transformtatso 1, 0 likarolo lenanezipcolor_encoded, shape_encoded, flavor_encoded 0, 0, 1 , 1, 0, 0 labels 0:apple, 1:orange labels 0, 1 clf DecisionTreeClassifier clf clf.fitlikarolo, lileibole Ho bolela esale pele sehlopha mala: khubelu0, sebopeho: chitja 0, tatso: tart 1 bolela esale pele clf.predict0, 0, 1 printpolele 0 : apole Ho bolela esale pele sehlopha mala: lamunu1, sebopeho: chitja 0, tatso: monate 0 bolepi clf.predict1, 0, 0 printprediction 1 : Orange Mona, re sebelisitse sekhetho sa sefate sa liqeto se sebelisang likarolo tse fanoeng ho khetholla pakeng tsa apole le lamunu. Likarolo tsa ho kenya li kentsoe ka linomoro, ebe li sebelisoa ka lileibole ho koetlisa mohlala. Joale, mohlala o ka sebelisoa ho bolela esale pele. 