MATH144 MOD 3 EXAM REVIEW
QUESTIONS WITH CORRECT ANSWERS
Which of the following is ALWAYS TRUE about considerations regarding the
implementation of k-means?
I. The k-means algorithm is sensitive to the starting positions of the initial centroid.
II. K-means can handle all types of variables.
---
I only
II only
both I and II
neither I nor II - Answer-I only
Which of the following is ALWAYS TRUE about unit of measurement?
I. To remedy the issue on unit measurement, rescaling of the attributes may be done by
dividing each
attribute value by its variance.
II. The choice for the unit of measurement of a particular object is important because it
directly affects
the cluster membership of the data points.
---
I only
II only
both I and II
neither I nor II - Answer-II only
In general, the following questions should be asked whenever performing diagnostics of
the results.
---
Are the clusters well separated from each other?
Do any of the clusters have only a few points?
Do any of the centroids appear to be too close to each other?
All of the Above - Answer-All of the above
The process of identifying the appropriate value of k is referred to as finding the "elbow"
of the WSS curve.
---
True
False - Answer-True
, Which of the following is TRUE about clustering?
---
Clustering analysis can help answer questions about natural groupings of the dataset.
By adding more variables about the customers, the task of finding meaningful groupings
in
clustering becomes more complex.
Clustering methods find the similarities between objects according to the object
attributes and
group the similar objects into clusters.
All of the Above - Answer-All of the above
This is an analytical technique that identifies k clusters of objects based on the objects9
proximity to the
center of the k groups where center is the arithmetic average of n-dimensional vector of
attributes.
---
K-modes
K-means
K-medians
None of the Above - Answer-K-means
Which of the following is an application of clustering?
---
Image processing
Plant classification
Customer Segmentation
All of the Above - Answer-All of the above
The following is ALWAYS TRUE about the k-means algorithm EXCEPT
---
The optimum number of clusters may be determined by examining the within sum of
squares for different values of k.
Convergence is reached when the computed centroids do not change or the centroids
and the assigned points oscillate back and forth from one iteration to the next.
The k-means results to an equal number of data points per cluster.
Centroids are recomputed for each newly defined cluster and data points are
reassigned based on the proximity to the newly computed centroids. - Answer-The k-
means results to an equal number of data points per cluster
Which of the following is TRUE about apriori algorithm?
QUESTIONS WITH CORRECT ANSWERS
Which of the following is ALWAYS TRUE about considerations regarding the
implementation of k-means?
I. The k-means algorithm is sensitive to the starting positions of the initial centroid.
II. K-means can handle all types of variables.
---
I only
II only
both I and II
neither I nor II - Answer-I only
Which of the following is ALWAYS TRUE about unit of measurement?
I. To remedy the issue on unit measurement, rescaling of the attributes may be done by
dividing each
attribute value by its variance.
II. The choice for the unit of measurement of a particular object is important because it
directly affects
the cluster membership of the data points.
---
I only
II only
both I and II
neither I nor II - Answer-II only
In general, the following questions should be asked whenever performing diagnostics of
the results.
---
Are the clusters well separated from each other?
Do any of the clusters have only a few points?
Do any of the centroids appear to be too close to each other?
All of the Above - Answer-All of the above
The process of identifying the appropriate value of k is referred to as finding the "elbow"
of the WSS curve.
---
True
False - Answer-True
, Which of the following is TRUE about clustering?
---
Clustering analysis can help answer questions about natural groupings of the dataset.
By adding more variables about the customers, the task of finding meaningful groupings
in
clustering becomes more complex.
Clustering methods find the similarities between objects according to the object
attributes and
group the similar objects into clusters.
All of the Above - Answer-All of the above
This is an analytical technique that identifies k clusters of objects based on the objects9
proximity to the
center of the k groups where center is the arithmetic average of n-dimensional vector of
attributes.
---
K-modes
K-means
K-medians
None of the Above - Answer-K-means
Which of the following is an application of clustering?
---
Image processing
Plant classification
Customer Segmentation
All of the Above - Answer-All of the above
The following is ALWAYS TRUE about the k-means algorithm EXCEPT
---
The optimum number of clusters may be determined by examining the within sum of
squares for different values of k.
Convergence is reached when the computed centroids do not change or the centroids
and the assigned points oscillate back and forth from one iteration to the next.
The k-means results to an equal number of data points per cluster.
Centroids are recomputed for each newly defined cluster and data points are
reassigned based on the proximity to the newly computed centroids. - Answer-The k-
means results to an equal number of data points per cluster
Which of the following is TRUE about apriori algorithm?
