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Data Analytics (Eng) / Data Analitika (Ing) - 344

Data Analytics (Eng) / Data Analitika (Ing) - 344

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The relationship between two features is described as follows: feature 2 increases when feature 1 increases up until a specific point, at which feature 2 decreases. The Pearson correlation will be

Close to zero

A large negative number

A large positive number

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Consider a heatmap where each row and column represent a feature, and the elements of the heatmap represent the Pearson correlation between two features. Comparing the columns of the heatmap is primarily performed to identify?

redundant features

100%

features with similar relationships

100%

representative features

features with similar scales

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When data points are closely packed together, it can be challenging distinguish the strength and direction of the relationship between the variables.

True

False

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Consider a target feature that is categorical, is it important to consider the sample size when deciding if a categorical feature is relevant?

Yes

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Identifying similar features from a heatmap where each row and column represent a feature, and the elements of the heatmap represent the Pearson correlation between two features is best described as a

Supervised Learning

Unsupervised Learning

Reinforcement Learning

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If the covariance between two variables is positive, what does this indicate?

The variables have a linear relationship

When one variable increases, the other variable tends to increase

100%

When one variable increases, the other variable tends to decrease

The variables have a non-linear relationship

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Which of the following best describes a redundant feature?