Question: Which sentence describes the entropy - based decision tree algorithm correctly? For the most informative attribute, its conditional entropy equals the basic entropy. H (

Which sentence describes the entropy-based decision tree algorithm correctly?
For the most informative attribute, its conditional entropy equals the basic entropy.
H(entropy) is used to quantify the impurity of a node in terms of class distribution.
The technique assumes that the relationship between the input variables (xs) and the output variable (Y) is
linear on the log-odds scale.
D The basic entropy of a node will be high if the data in it belong to a single class.
Which sentence describes the entropy - based

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