BUAL 5610 Quiz 2

Select one INCORRECT sentence about resampling methods
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Select one INCORRECT sentence about resampling methods
K-nearest neighbors is an example of resampling methods.
The following is the process of k-fold cross validation. Select one INCORRECT step.
4. Repeat steps 2 and 3 for k times, taking out the same part for validation.
Select the correct sentence describing ensemble methods.
For classification (qualitative outcomes), we can either take the majority classes or take the average of the probabilities and then classify accordingly.
Select the correct sentence describing bootstrapping.
Bootstrapping involves resampling of the observed dataset.
Suppose we produce 4 bootstrapped samples from a dataset containing red and green classes. We then apply a decision tree to each bootstrapped sample and, for a specific set of predictors X, produce 4 estimates of P(Class is Red | X):
0.1, 0.8, 0.9, and 0.95.
What is the final classification for this set of predictors?
red
Select the INCORRECT sentence describing the random forest method.
Each time the tree makes a split, it should considers all predictors.
Select the INCORRECT sentence describing pros and cons of ensemble methods.
Ensemble models suffer from overfitting.
Select the correct sentence describing k-nearest neighbor (kNN) classifiers.
We can use Euclidean as the distance metric.
Select the correct sentence describing how to choose k for a k-nearest neighbors (kNN) classifier.
If k is too small, the model will be sensitive to noise datapoints.
Select the INCORRECT sentence describing pros and cons of k-nearest neighbors (kNN) method.
kNN works well with categorical predictors.
Select the INCORRECT sentence describing the pros and cons of Naive Bayes method.Naive Bayes method is not robust to noise points.Select the correct sentence describing the core ideas of support vector classifiers.The classification of a point depends on which side of the line (or hyperplane) it falls on.Select the INCORRECT sentence describing support vector machine classifier.Transformation of data produces a non-linear plane in the transformed space, but a linear decision boundary in the original space.Select the INCORRECT sentence describing the pros and cons of support vector machine classifiers.It is not effective in high dimensional spaces