Question 1

Which is a characteristic of random forests?

Accepted Answer

A)  They are nonparametric 
B)  They are nonlinear 
C)  They are robust against multicollinearity 
D)  All of the above 
A)  They are nonparametric 
B)  They are nonlinear 
C)  They are robust against multicollinearity 
D)  All of the above D

Question 2

The same random forest model with the randomForest command will always return the same solution on each run of the model

Accepted Answer

A) True 
 B)False  False

Question 3

The randomForest command is ….

Accepted Answer

A)  Part of the "randomForest" package and needs explicit installation in R. 
B)  Part of R's built-in "stats" package and needs no explicit installation. 
C)  Part of R's built-in "graphics" package and needs no explicit installation. 
D)  Part of R's built-in "base" package and needs no explicit installation. 
A)  Part of the "randomForest" package and needs explicit installation in R. 
B)  Part of R's built-in "stats" package and needs no explicit installation. 
C)  Part of R's built-in "graphics" package and needs no explicit installation. 
D)  Part of R's built-in "base" package and needs no explicit installation. A

Question 4

If RFclass is an object created by a randomForest classification model, what is RFclass$proximity?

Accepted Answer

A)  An element with coefficients showing the average frequency that pairs of observations follow the same path and wind up in the same terminal node. 
B)  An element s with coefficients showing the intercorrelation of variables in the model 
C)  An element with coefficients showing Euclidean distance between observations 
D)  An element with coefficients showing Euclidean distance between predictors 
A)  An element with coefficients showing the average frequency that pairs of observations follow the same path and wind up in the same terminal node. 
B)  An element s with coefficients showing the intercorrelation of variables in the model 
C)  An element with coefficients showing Euclidean distance between observations 
D)  An element with coefficients showing Euclidean distance between predictors

Question 5

Fill-In. What is the name of the package which can return up to seven different variable importance criteria for a random forest model, or importance by a combination of criteria?

Accepted Answer

The answer of Fill-In. What is the name of the...

Question 6

With random forests, categorical variables may be used as independent or dependent variables and may be coded as characters or as numbers.

Accepted Answer

A) True 
 B)False

Question 7

If RFclass is an object created by the randomForest command, what is RFclass$predicted?

Accepted Answer

A)  A variable called "predicted" in the data frame used to create RFclass 
B)  An automatically generated element of RFclass containing predictions of the outcome variable 
C)  A variable added to RFclass after using the predict command 
D)  A variable added to the data frame used to create RFclass after using the predict command 
A)  A variable called "predicted" in the data frame used to create RFclass 
B)  An automatically generated element of RFclass containing predictions of the outcome variable 
C)  A variable added to RFclass after using the predict command 
D)  A variable added to the data frame used to create RFclass after using the predict command

Question 8

In random forest solutions, there is no way to print a graph showing the "typical" tree.

Accepted Answer

A) True 
 B)False

Question 9

What will increasing the size of the "minbucket" option do in random forests?

Accepted Answer

A)  No effect 
B)  Increase the number of trees used for the solution 
C)  Trees in the forest will be more complex (more splits) 
D)  Trees in the forest will be less complex (fewer splits) 
A)  No effect 
B)  Increase the number of trees used for the solution 
C)  Trees in the forest will be more complex (more splits) 
D)  Trees in the forest will be less complex (fewer splits)

Question 10

Fill-In. Developing a random forest model with a training subset of the data and validating it with an OOB (out of box) subset is called ___________________________________

Accepted Answer

The answer of Fill-In. Developing a random forest model with...

Question 11

Which is an "ensemble" method?

Accepted Answer

A)  Classification trees 
B)  Regression trees 
C)  Random forests 
D)  None of the above 
A)  Classification trees 
B)  Regression trees 
C)  Random forests 
D)  None of the above

Question 12

Is this a true statement: "The more trees in a random forest solution, the better the model performance."

Accepted Answer

A) True 
 B)False

Question 13

If RFclass is an output object created by the randomForest command, typing plot(RFclass) will generate an error rate plot. What is this plot used for?

Accepted Answer

A)  Used to determine the needed size of minbucket 
B)  Used to determine the needed size of mtry 
C)  Used to determine the needed size of ntree 
D)  None of the above 
A)  Used to determine the needed size of minbucket 
B)  Used to determine the needed size of mtry 
C)  Used to determine the needed size of ntree 
D)  None of the above

Question 14

The "ctree" package implements conditional inference trees. What is the distinguishing aspect of a cforest solution compared to a randomForest solution?

Accepted Answer

A)  Conditional inference trees use partial correlations as splitting criteria. 
B)  Conditional inference trees use factor analysis to form clusters. 
C)  Conditional inference trees use p values from significance tests as splitting criteria 
D)  Conditional inference trees do not incorporate a random element. 
A)  Conditional inference trees use partial correlations as splitting criteria. 
B)  Conditional inference trees use factor analysis to form clusters. 
C)  Conditional inference trees use p values from significance tests as splitting criteria 
D)  Conditional inference trees do not incorporate a random element.

Question 15

Which is NOT a use of random forests?

Accepted Answer

A)  prediction of outcomes; organizing observations into classes; 
B)  partitioning between- and within- variance components 
C)  organizing observations into classes 
D)  selection of the most important predictor variables 
A)  prediction of outcomes; organizing observations into classes; 
B)  partitioning between- and within- variance components 
C)  organizing observations into classes 
D)  selection of the most important predictor variables

Question 16

What is the primary model performance metric for random forest regression models?

Accepted Answer

A)  Accuracy 
B)  Gini Index 
C)  R-Squared 
D)  Mean square error 
A)  Accuracy 
B)  Gini Index 
C)  R-Squared 
D)  Mean square error

Question 17

What does a "confusion table" show?

Accepted Answer

A)  Overlap of independent variables with each other 
B)  Overlap of independent variables with the dependent variable 
C)  The error rate in a regression random forest model 
D)  The error rate in a classification random forest model 
A)  Overlap of independent variables with each other 
B)  Overlap of independent variables with the dependent variable 
C)  The error rate in a regression random forest model 
D)  The error rate in a classification random forest model

Question 18

In random forest classification models, what is a metric for variable importance?

Accepted Answer

A)  MeanDecreaseAccuracy 
B)  MeanDecreaseGini 
C)  Both A and B 
D)  Neither A nor B 
A)  MeanDecreaseAccuracy 
B)  MeanDecreaseGini 
C)  Both A and B 
D)  Neither A nor B

Question 19

What does the "mtry" option do in random forests?

Accepted Answer

A)  Specifies the number of iterations in the solution 
B)  Specifies the number of trees to use in the forest 
C)  Specifies the number of predictors to consider at each split in a tree 
D)  There is no such option 
A)  Specifies the number of iterations in the solution 
B)  Specifies the number of trees to use in the forest 
C)  Specifies the number of predictors to consider at each split in a tree 
D)  There is no such option

Which is a characteristic of random forests?

The same random forest model with the randomForest command will always return the same solution on each run of the model

The randomForest command is ….

If RFclass is an object created by a randomForest classification model, what is RFclass$proximity?

Fill-In. What is the name of the package which can return up to seven different variable importance criteria for a random forest model, or importance by a combination of criteria?

With random forests, categorical variables may be used as independent or dependent variables and may be coded as characters or as numbers.

If RFclass is an object created by the randomForest command, what is RFclass$predicted?

In random forest solutions, there is no way to print a graph showing the "typical" tree.

What will increasing the size of the "minbucket" option do in random forests?

Fill-In. Developing a random forest model with a training subset of the data and validating it with an OOB (out of box) subset is called ___________________________________

Which is an "ensemble" method?

Is this a true statement: "The more trees in a random forest solution, the better the model performance."

If RFclass is an output object created by the randomForest command, typing plot(RFclass) will generate an error rate plot. What is this plot used for?

The "ctree" package implements conditional inference trees. What is the distinguishing aspect of a cforest solution compared to a randomForest solution?

Which is NOT a use of random forests?

What is the primary model performance metric for random forest regression models?

What does a "confusion table" show?

In random forest classification models, what is a metric for variable importance?

What does the "mtry" option do in random forests?

Using and Abusing Data Analytics in Social Science

Statistical Analytics With R Part 1

Statistical Analytics With R Part 2

Classification and Regression Trees in R

Modeling and Machine Learning

Neural Network Models and Deep Learning

Network Analysis

Text Analytics

Filters

Exam 5: Random Forests

Which is a characteristic of random forests?

The same random forest model with the randomForest command will always return the same solution on each run of the model

The randomForest command is ….

If RFclass is an object created by a randomForest classification model, what is RFclass$proximity?

Fill-In. What is the name of the package which can return up to seven different variable importance criteria for a random forest model, or importance by a combination of criteria?

With random forests, categorical variables may be used as independent or dependent variables and may be coded as characters or as numbers.

If RFclass is an object created by the randomForest command, what is RFclass$predicted?

In random forest solutions, there is no way to print a graph showing the "typical" tree.

What will increasing the size of the "minbucket" option do in random forests?

Fill-In. Developing a random forest model with a training subset of the data and validating it with an OOB (out of box) subset is called ___________________________________

Which is an "ensemble" method?

Is this a true statement: "The more trees in a random forest solution, the better the model performance."

If RFclass is an output object created by the randomForest command, typing plot(RFclass) will generate an error rate plot. What is this plot used for?

The "ctree" package implements conditional inference trees. What is the distinguishing aspect of a cforest solution compared to a randomForest solution?

Which is NOT a use of random forests?

What is the primary model performance metric for random forest regression models?

What does a "confusion table" show?

In random forest classification models, what is a metric for variable importance?

What does the "mtry" option do in random forests?

Using and Abusing Data Analytics in Social Science

Statistical Analytics With R Part 1

Statistical Analytics With R Part 2

Classification and Regression Trees in R

Modeling and Machine Learning

Neural Network Models and Deep Learning

Network Analysis

Text Analytics

Filters