DM week 10
- Created by: mariolarc
- Created on: 14-05-21 10:59
Other questions in this quiz
2. Which of the following statements about dimensionality reduction is false?
- Dimensionality reduction is mainly a data preparation technique.
- Dimensionality reduction techniques must be linear transformations.
- Feature selection and PCA are both dimensionality reduction techniques.
- Dimensionality reduction allows transforming a data set into a new one with a potentially significantly smaller number of features, so that the new data set retains some useful properties of the original data set.
3. Backward feature selection is typically:
- A probabilistic approach.
- A practical approach.
- A time-consuming approach.
- A regression approach.
4. Which of the following statements about principal component analysis is false?
- The number of principal components is as most equal to the number of features.
- Identifies directions with low variance.
- Two different principal components are orthogonal to each other.
- Principal component analysis is a linear transformation.
5. Consider a classification problem with one target attribute and categorical input attributes. Which of the following is the least relevant for effectively performing feature selection to solve this classification problem?
- Remove an input attribute if it is highly correlated with another input attribute.
- Remove an input attribute x if the mutual information between the target attribute and x is low.
- Remove input attributes with a small set of possible values
- Remove input attributes which are independent of the target attribute.
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