Question

Which of the following two statements are correct?

		The prediction performance of a model increases monotonically with the number of features used in the model
		Clustering in a high dimensional space is challenging because there tends to be limited variation in pairwise distance of data points
		The amount of data needed to produce reliable results grows exponentially with the number of dimensions
		Suppose we collect a dataset with a billion users and each user has 10 features, we may run into the issue of curse of dimensionality

Answer 1

The prediction performance of a model increases monotonically with the number of features used in the model is false

because the prediction performance will decrease with the increase of models

Clustering in a high dimensional space is challenging because there tends to be limited variation in pairwise distance of data points is true

The amount of data needed to produce reliable results grows exponentially with the number of dimensions is also true statement

Suppose we collect a dataset with a billion users and each user has 10 features, we may run into the issue of curse of dimensionality is false

because curse of dimensionality occures when user dataset has multiple dimensions but here dimesions not mentioned so this is false

statement 2 and 3 are correct choices

so the answers are

Clustering in a high dimensional space is challenging because there tends to be limited variation in pairwise distance of data points

The amount of data needed to produce reliable results grows exponentially with the number of dimensions

hope the answer is helpful

please dont downvote