Question 1

What will be the output of the following code: Figure from the original question paper What will be the numerical value in the output array of the following code: import numpy as np from sklearn.preprocessing import StandardScaler from sklearn.impute import SimpleImputer from sklearn.pipeline import Pipeline X_train = [[1],[2],[3],[np.nan], [4], [np.nan], [5]] pipe = Pipeline(steps = [('impute', SimpleImputer(strategy='mean')), ('scale', StandardScaler())]) pipe.fit(X_train) print(pipe[0].statistics_) Given below a y_train list which consists of coffee order’s preference by the customers in a cafe. y_train = [['large', 'cold'], ['small', 'cold'], ['small', 'hot'], ['large', 'hot']] MultiLabelBinarizer from sklearn library has been used to convert the y_train into numbers, so which of the following option matches with the output of the following code ? from sklearn.preprocessing import MultiLabelBinarizer mlb = MultiLabelBinarizer(classes=['cold', 'hot', 'large', 'small']) print(mlb.fit_transform(y_train))