DATA MINING FINAL QUESTIONS &
ANSWERS
The k-Means Clustering is a data mining model that predicts values. - ANSWERfalse
All of the attribute values must be numeric if one wants to use the k-Means Clustering
model. - ANSWERtrue
The k-Means clustering technique for data analysis is ideal for _________.
machine learning
prediction
time series forecasting
segmentation - ANSWERsegmentation
The averages for each attribute in each cluster created by a k-Means model are called
_______.
midpoints
complex means
centroids
simple means - ANSWERcentroids
The k in k-Means indicates ________.
the intercept for the model
the number of clusters desired
the coefficient of the dependent variable
the coefficient of the independent variable - ANSWERthe number of clusters desired
True or false: The cluster number assigned to each cluster in a k-Mean model indicates
the relative importance of each cluster when compared to the others. - ANSWERfalse
To view which observations are assigned to each cluster in a k-Means model in
RapidMiner, use the ________ feature. - ANSWERfolder view
To prevent a k-Means model for a large data set from taking a long time to run, you can
adjust the _________ parameter in RapidMiner.
divergence
max runs
measure types
start values - ANSWERmax runs
To examine all records in one specific cluster in RapidMiner, use a ______________
operator.
Sample
Filter Examples
, Cluster
Select Attributes - ANSWERfilter examples
To see the size of each cluster in RapidMiner, click the ______________ icon in
Results view.
Folder View
Description
Centroid Table
Graph - ANSWERdescription
Discriminant analysis, k-Nearest Neighbors, and Naïve Bayes are all datamining models
used to __________ data values.
categorize
predict & categorize
guess
predict - ANSWERpredict & categorize
The attribute you want to predict in a predictive model is called a(n) _________.
dependent variable
independent variable
identifying variable
category variable - ANSWERdependent variable
In linear regression, the x variable is the independent variable's ________ -
ANSWERvalue
In linear regression, the b variable is the model's ________. - ANSWERintercept
coefficient
In linear regression, p-values larger than alpha indicate that their corresponding
independent variables are __________. - ANSWERnot statistically significant
To remove out-of-range values from a scoring data set in RapidMiner, use a
___________ operator. - ANSWERfilter examples
To calculate the sum total of all predictions in a linear regression operator in
RapidMiner, use a(n) __________ operator.
Sum
Total
Aggregate
Summarize - ANSWERaggregate
What data type must be assigned to the dependent variable in RapidMiner when
building linear regression models?
Label
ANSWERS
The k-Means Clustering is a data mining model that predicts values. - ANSWERfalse
All of the attribute values must be numeric if one wants to use the k-Means Clustering
model. - ANSWERtrue
The k-Means clustering technique for data analysis is ideal for _________.
machine learning
prediction
time series forecasting
segmentation - ANSWERsegmentation
The averages for each attribute in each cluster created by a k-Means model are called
_______.
midpoints
complex means
centroids
simple means - ANSWERcentroids
The k in k-Means indicates ________.
the intercept for the model
the number of clusters desired
the coefficient of the dependent variable
the coefficient of the independent variable - ANSWERthe number of clusters desired
True or false: The cluster number assigned to each cluster in a k-Mean model indicates
the relative importance of each cluster when compared to the others. - ANSWERfalse
To view which observations are assigned to each cluster in a k-Means model in
RapidMiner, use the ________ feature. - ANSWERfolder view
To prevent a k-Means model for a large data set from taking a long time to run, you can
adjust the _________ parameter in RapidMiner.
divergence
max runs
measure types
start values - ANSWERmax runs
To examine all records in one specific cluster in RapidMiner, use a ______________
operator.
Sample
Filter Examples
, Cluster
Select Attributes - ANSWERfilter examples
To see the size of each cluster in RapidMiner, click the ______________ icon in
Results view.
Folder View
Description
Centroid Table
Graph - ANSWERdescription
Discriminant analysis, k-Nearest Neighbors, and Naïve Bayes are all datamining models
used to __________ data values.
categorize
predict & categorize
guess
predict - ANSWERpredict & categorize
The attribute you want to predict in a predictive model is called a(n) _________.
dependent variable
independent variable
identifying variable
category variable - ANSWERdependent variable
In linear regression, the x variable is the independent variable's ________ -
ANSWERvalue
In linear regression, the b variable is the model's ________. - ANSWERintercept
coefficient
In linear regression, p-values larger than alpha indicate that their corresponding
independent variables are __________. - ANSWERnot statistically significant
To remove out-of-range values from a scoring data set in RapidMiner, use a
___________ operator. - ANSWERfilter examples
To calculate the sum total of all predictions in a linear regression operator in
RapidMiner, use a(n) __________ operator.
Sum
Total
Aggregate
Summarize - ANSWERaggregate
What data type must be assigned to the dependent variable in RapidMiner when
building linear regression models?
Label
