DSCI 4520 EXAM 2 QUESTIONS WITH VERIFIED
ANSWERS
Which statement is INCORRECT about the structure of decision trees? - Answers -
Numerical attributes cannot be tested in the tree
The following chart shows the prediction error of a decision tree based on the training
set and validation set as functions of the number of splits. What phenomenon is causing
the gap between the two curves at higher numbers of splits? - Answers - Model
overfitting
What statement is correct about the point of maximum entropy/Gini index? - Answers -
Impurity of a node is maximized
We are building a decision tree to predict loan default with four predictors: Age, Income,
Gender, and Credit Score. For the first split, we have calculated the Gini index of each
test. Based on the following information, which predictor is the best for the first split? -
Answers - Income
In building a decision tree, a common strategy for selecting an attribute for splitting is to
choose the attribute (feature) that results in the lowest degree of certainty after the split.
- Answers - False
A decision tree can be pre- or post-pruned to avoid underfitting a classification and
regression tree. - Answers - False
Which of the following technique is NOT useful for preventing over-fitting a decision
tree? - Answers - Adding duplicate records
The following chart shows the prediction error of a decision tree based on the training
set and validation set as functions of the number of splits. To avoid overfitting what is
the best number of splits? - Answers - 5
A decision tree for classification provides a set of IF-THEN rules. - Answers - True
The overall goal of building a decision tree for classification is to create leaves that are
purer in terms of class labels. - Answers - True
What is the primary method to avoid underfitting when you are training a classification
and regression tree model? - Answers - Adding the number of tests (splits)
ANSWERS
Which statement is INCORRECT about the structure of decision trees? - Answers -
Numerical attributes cannot be tested in the tree
The following chart shows the prediction error of a decision tree based on the training
set and validation set as functions of the number of splits. What phenomenon is causing
the gap between the two curves at higher numbers of splits? - Answers - Model
overfitting
What statement is correct about the point of maximum entropy/Gini index? - Answers -
Impurity of a node is maximized
We are building a decision tree to predict loan default with four predictors: Age, Income,
Gender, and Credit Score. For the first split, we have calculated the Gini index of each
test. Based on the following information, which predictor is the best for the first split? -
Answers - Income
In building a decision tree, a common strategy for selecting an attribute for splitting is to
choose the attribute (feature) that results in the lowest degree of certainty after the split.
- Answers - False
A decision tree can be pre- or post-pruned to avoid underfitting a classification and
regression tree. - Answers - False
Which of the following technique is NOT useful for preventing over-fitting a decision
tree? - Answers - Adding duplicate records
The following chart shows the prediction error of a decision tree based on the training
set and validation set as functions of the number of splits. To avoid overfitting what is
the best number of splits? - Answers - 5
A decision tree for classification provides a set of IF-THEN rules. - Answers - True
The overall goal of building a decision tree for classification is to create leaves that are
purer in terms of class labels. - Answers - True
What is the primary method to avoid underfitting when you are training a classification
and regression tree model? - Answers - Adding the number of tests (splits)
