Data Mining Exam Questions and
Answers
Multiplot uses two different variables and graphs them together. This is good for
business uses because you are able to see the relationship and the trends of two
variables on top of eachother.
Link analysis is a way to see how variables are related to eachother. It looks to see
what they have in common, and what they don't have in common. This is important
for business use because it helps you quickly identify why relationships do or do not
exist.
When is it appropriate to use a histogram? - Answer-To display "how many" of each
value occur in a data set
When is it appropriate to use a bar graph? - Answer-For categorical data
When is it appropriate to use a scatterplot? - Answer-For demonstrating a
relationship between two numerical variables
When is it appropriate to use a line graph? - Answer-For data involving time series
The beta coefficients of a logistic regression model... - Answer-May be different for a
1 unit change of an independent variable value (say from 3-4 than 5-6, while holding
other model features constant)
One approach to developing models when the target variable contains a rare class is
___ - Answer-Oversampling
What is true of logistic regression models? - Answer-It is a supervised model that
uses a categorical target variable
Assessment for classification models include - Answer-Lift
Classification matrix (confusion matrix)
Misclassification rate
Error metrics
What are the axes of a ROC (Receiver operating characteristic) curve? - Answer-
Vertical axis: % of true positives
Horizontal axis: % of false positives
What is true of k-nearest neighbor models? - Answer-Either: (not sure)
It is a supervised model that uses a specified model for finding "similar" records
It is an unsupervised model that somehow magically measures records' proximity
It is a supervised model that requires model that requires no target variable because
it places records close together
, In k-nearest-neighbor classification, choosing low values of k results in - Answer-
Either: (not sure)
Predicting the most frequent class label
Avoiding over-smoothing
Missing local noise in the training data
none of the above
At a minimum, running a k-nearest neighbor model requires - Answer-Setting the
number of neighbors to compare records to
A k-nearest neighbor model ___ - Answer-Is one of the models in IBM SPSS
Modeler and SAS EM
May be referred to as Case Based Reasoning
Evaluates on k neighbors
One method to possibly reduce the dimensionality of a supervised model is ___ -
Answer-To use the 5th dimension
To use principal components with eignvalues > 1
To use principal components with negative eignvalues
One should ___ for clustering - Answer-c &d
Clustering algorithms seek to create clusters such that the ___ is large compared to
the ___ - Answer-Between-cluster variation, within-cluster variation
Clustering requires standardization. One way to do standardization is using the min-
max equation (value of interest - minimum)/Range. Given a particular predictor has a
mean of 10, minimum value of 8 and a maximum value of 12, provide the range and
use the min-max equation to standardize the following two values.
Standardize the value 9:
Standardize the value 11: - Answer-9 = (9-8)/(12-8) = 1/4
11 = (11-8)/(12-8) = 3/4
clustering is in the __ category of data mining - Answer-pg 12 of textbook
When referring to Kohonen/SOM clustering models, SOM is - Answer-Self-
organizing map
the most common clustering method is ___ - Answer-k-means
what is a major difference between the data mining tasks of clustering and
classification - Answer-classification is a supervised data mining task where as
clustering is an unsupervised data mining task
Answers
Multiplot uses two different variables and graphs them together. This is good for
business uses because you are able to see the relationship and the trends of two
variables on top of eachother.
Link analysis is a way to see how variables are related to eachother. It looks to see
what they have in common, and what they don't have in common. This is important
for business use because it helps you quickly identify why relationships do or do not
exist.
When is it appropriate to use a histogram? - Answer-To display "how many" of each
value occur in a data set
When is it appropriate to use a bar graph? - Answer-For categorical data
When is it appropriate to use a scatterplot? - Answer-For demonstrating a
relationship between two numerical variables
When is it appropriate to use a line graph? - Answer-For data involving time series
The beta coefficients of a logistic regression model... - Answer-May be different for a
1 unit change of an independent variable value (say from 3-4 than 5-6, while holding
other model features constant)
One approach to developing models when the target variable contains a rare class is
___ - Answer-Oversampling
What is true of logistic regression models? - Answer-It is a supervised model that
uses a categorical target variable
Assessment for classification models include - Answer-Lift
Classification matrix (confusion matrix)
Misclassification rate
Error metrics
What are the axes of a ROC (Receiver operating characteristic) curve? - Answer-
Vertical axis: % of true positives
Horizontal axis: % of false positives
What is true of k-nearest neighbor models? - Answer-Either: (not sure)
It is a supervised model that uses a specified model for finding "similar" records
It is an unsupervised model that somehow magically measures records' proximity
It is a supervised model that requires model that requires no target variable because
it places records close together
, In k-nearest-neighbor classification, choosing low values of k results in - Answer-
Either: (not sure)
Predicting the most frequent class label
Avoiding over-smoothing
Missing local noise in the training data
none of the above
At a minimum, running a k-nearest neighbor model requires - Answer-Setting the
number of neighbors to compare records to
A k-nearest neighbor model ___ - Answer-Is one of the models in IBM SPSS
Modeler and SAS EM
May be referred to as Case Based Reasoning
Evaluates on k neighbors
One method to possibly reduce the dimensionality of a supervised model is ___ -
Answer-To use the 5th dimension
To use principal components with eignvalues > 1
To use principal components with negative eignvalues
One should ___ for clustering - Answer-c &d
Clustering algorithms seek to create clusters such that the ___ is large compared to
the ___ - Answer-Between-cluster variation, within-cluster variation
Clustering requires standardization. One way to do standardization is using the min-
max equation (value of interest - minimum)/Range. Given a particular predictor has a
mean of 10, minimum value of 8 and a maximum value of 12, provide the range and
use the min-max equation to standardize the following two values.
Standardize the value 9:
Standardize the value 11: - Answer-9 = (9-8)/(12-8) = 1/4
11 = (11-8)/(12-8) = 3/4
clustering is in the __ category of data mining - Answer-pg 12 of textbook
When referring to Kohonen/SOM clustering models, SOM is - Answer-Self-
organizing map
the most common clustering method is ___ - Answer-k-means
what is a major difference between the data mining tasks of clustering and
classification - Answer-classification is a supervised data mining task where as
clustering is an unsupervised data mining task
