Question: In contrast to supervised learning, data preprocessing (scaling, normalization, non-linear variance-stabilizing transformations, identifying relevant features/combinations of variables, etc) ismuch less important in unsupervised learning and

In contrast to supervised learning, data preprocessing (scaling, normalization, non-linear variance-stabilizing transformations, identifying relevant features/combinations of variables, etc) ismuch less important in unsupervised learning and is not worth investing much time into: the clusters are the clusters are the clusters, and the algorithms will just find the latter (if those are presentat all).

( ) True

( ) False

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