Question : Select the correct statement which can be applied to feature selection?
1. May Improve performance of classification algorith006D 2. Classification algorithm may not scale up to the size of the full feature set either in sample or time 3. Access Mostly Uused Products by 50000+ Subscribers 4. Cheaper to collect a reduced set of predictors 5. Safer to collect a reduced set of predictors
The method based on principal component analysis (PCA) evaluates the features according to
1. the projection of the largest eigenvector of the correlation matrix on the initial dimensions 2. according to the magnitude of the components of the discriminate vector 3. Access Mostly Uused Products by 50000+ Subscribers 4. None of the above
Explanation: Feature Selection: The method based on principal component analysis (PCA) evaluates the features according to the projection of the largest eigenvector of the correlation matrix on the initial dimensions, the method based on Fisher's linear discriminate analysis evaluates. Them according to the magnitude of the components of the discriminate vector.
Question :
mutual information___________
1. can measure arbitrary relations between variables and it do not depend on transformations acting on the different variables. 2. cannot take care of arbitrary relations between the pattern coordinates and the different classes. 3. Access Mostly Uused Products by 50000+ Subscribers 4. None of the above
Explanation: A linear scaling of the input variables (that may be caused by a change of units for the measurements) is sufficient to modify the PCA results. Feature selection methods that are sufficient for simple distributions of the patterns belonging to different classes can fail in classification tasks with complex decision boundaries. In addition, methods based on a linear dependence (like the correlation) cannot take care of arbitrary relations between the pattem coordinates and the different classes. On the contrary, the mutual information can measure arbitrary relations between variables and it does not depend on transformations acting on the different variables.
Question : Which of the following is an example of Gaussian distribution application? 1. If the average man is 175 cm tall with a variance of 6 cm, what is the probability that a man found at random will be 183 cm tall? 2. If the average man is 175 cm tall with a variance of 6 cm and the average woman is 168 cm tall with a variance of 3cm, what is the probability that the average man will be shorter than the average woman? 3. Access Mostly Uused Products by 50000+ Subscribers order to ensure that the 99% of all cans have a weight of at least 250 grams? 4. 1 and 2 only 5. Both 1 and 2