[amp_mcq option1=”LabelEncoder” option2=”LabelBinarizer” option3=”DictVectorizer” option4=”Imputer” correct=”option4″]
The correct answer is D. Imputer.
Imputer is a class in scikit-learn that is responsible for filling the holes using a strategy based on the mean, median, or frequency. It can be used to fill missing values in a dataset.
LabelEncoder is a class in scikit-learn that is used to encode labels. It can be used to convert categorical data into numerical data.
LabelBinarizer is a class in scikit-learn that is used to binarize labels. It can be used to convert categorical data into binary data.
DictVectorizer is a class in scikit-learn that is used to vectorize a dictionary. It can be used to convert a dictionary of features into a vector of features.