Question 1

The concept behind neural networks is to

Accepted Answer

A)  identify a function that accurately maps a set of input values to a corresponding set of output values
B)  simulate how the classification process works
C)  estimate a linear relationship between input and output values
D)  develop a relationship that maps input values to an arbitrary set of output values A

Question 2

The k-nearest neighbor classification technique

Accepted Answer

A)  identifies the k observations in the training data that are most similar to a new observation we want to classify
B)  sorts the data in an increasing order
C)  sorts the data in a decreasing order
D)  works very much like the ranking algorithm A

Question 3

In preparation for mining an analyst should

Accepted Answer

A)  explore the relationships between variables
B)  verify completeness and accuracy of the data
C)  clean the data addressing missing values,errors,etc.
D)  all of the above D

Question 4

Exhibit 10.1
The following questions are based on the problem description,regression results,and the Analytic Solver Platform Discriminant Analysis report below.
A college admissions officer wants to evaluate graduate school applicants based on their GMAT scores,verbal and quantitative.Students are classified as either successful or not-successful in their graduate studies.The officer has data on 20 current students,ten of whom are doing very well Group 1)and ten who are not Group 2).
   Unpooled Estimates of within-group Covariance matrices are used,assuming they are different.
Group Centroids
Group Quantitative Verbal
1 683.8 654.2
2 610.7 605.7
 $\text { Classitication Matrix }$
$\begin{array}{cccc} 
\text { Actual / Predicted }
& \text { Group1 } & \text { Group2 } & \text { Total } & \% \text { correct } \
\hline \text { Group1 } & 9 & 1 & 1 & 90.00 \% \
&& & 0 & \
\text { Group2 }&  2 &8 & 1 & 80.00 \% \
&  &  & 0 & \\
\text { Total } & 1 & 9& 2 & 85.00 \%\
&1&&0 
\end{array}$ 
-Refer to Exhibit 10.1.What is the verbal test score value of the group centroid for group 1?

Accepted Answer

A)  683.8
B)  654.2
C)  610.7
D)  605.7

Question 5

A provides a visual summary of the improvements that a data mining project provides on a binary classification problem compared to a random guess

Accepted Answer

A)  lift chart
B)  Pareto chart
C)  Gantt chart
D)  histogram

Question 6

Techniques)used in prediction step of data mining include

Accepted Answer

A)  regression analysis
B)  the k'th largest neighbor technique
C)  neural networks
D)  all of the above

Question 7

A algorithm is used during the training process to adjust weights in a neural network

Accepted Answer

A)  backpropagation
B)  branch-and-bound
C)  Simplex
D)  cutting plane

Question 8

Exhibit 10.2
The following questions are based on the problem description,spreadsheet,and the Analytic Solver Platform Discriminant Analysis report below.
A college admissions officer wants to evaluate graduate school applicants based on their GMAT scores,verbal and quantitative.Students are classified as either successful Group 1),marginally successful Group 2)or not- successful Group 3)in their graduate studies.The officer has data on 20 current students,7 successful Group 1),6 marginally successful Group 2)and 7 not successful Group 3).
  Discriminant Analysis Report
October 1,2013 4:22:38 PM
Unpooled Estimates of within-group Covariance matrices are used,assuming they are different.
 $\begin{array}{lll}
\text {Group}\
\text { Centroids}\
\text { Group } & \text { Quantitative } & \text { Verbal } \
\hline 1 & 697.7142857 & 650.4285714 \
2 & 647.8571429 & 630.7142857 \
3 & 5876666667 & 6051666667
\end{array}$
 $\text {Group}$
$\text {Frenuencies}$
$\begin{array}{cr}
\text { Group } & \begin{array}{r}
\text { Relative } \
\text { Frequency }
\end{array} \
\hline 1 & 35.00 \% \
2 & 35.00 \% \
3 & 30.00\%
\end{array}$
 Training Sample Classification
Mahalanobis Distances
  $\text {Classification}$
$\text {Matrix}$
$\begin{array}{llllll}
\text { Actual / Predicted } & \text { Group1 } & \text { Group2 } & \text { Group3 } & \text { Total } & \% \text { correct } \
\hline \text { Group1 } & 6 & 1 & 0 & 7 & 85.71 \% \
\text { Group2 } & 0 & 7 & 0 & 7 & 100.00 \% \
\text { Group3 } & 0 & 0 & 6 & 6 & 100.00 \% \
\text { Total } & 6 & 8 & 6 & 2 & 95.00 \%
\end{array}$

-Refer to Exhibit 10.2.Based on the analysis presented in the spreadsheet,what percentage of the observations were correctly classified?

Accepted Answer

A)  80%
B)  85%
C)  95%
D)  100%

Question 9

In using neural networks,an analyst must decide and _

Accepted Answer

A)  how many hidden layers to use and how many nodes to use in each of the hidden layers
B)  how accurate the prediction should be and how many iterations to use
C)  how many nodes to use and how much time to allow for simulation
D)  how many iterations to use and what is the limit on the budget constraint

Question 10

Neural networks classification methodology

Accepted Answer

A)  is one of the options available in XLMiner Excel add-in
B)  is superior to other classification schemes
C)  is inferior to other classification schemes
D)  produces results that are identical to the outcomes of the DA technique

Question 11

An Excel add-in tool used for data mining is called

Accepted Answer

A)  XL Miner
B)  GS4
C)  XML
D)  Data Miner

Question 12

Suppose that two variables are found to be significantly correlated.A researcher may

Accepted Answer

A)  remove one variable from the data set
B)  replace the two variables by their product
C)  replace the two variables by their squared difference
D)  remove both variables from the data set

Question 13

Before effectively applying the k nearest neighbor classification technique,the variables need to be

Accepted Answer

A)  standardized
B)  normalized
C)  randomized
D)  trimmed

Question 14

Two common ways of measuring impurity are and _

Accepted Answer

A)  the Gini index and the entropy measure
B)  the fraction of pure data and the enthaply index
C)  the fraction of contaminated data and the entropy index
D)  the fraction of real data and the data purity coefficient

Question 15

Exhibit 10.1
The following questions are based on the problem description,regression results,and the Analytic Solver Platform Discriminant Analysis report below.
A college admissions officer wants to evaluate graduate school applicants based on their GMAT scores,verbal and quantitative.Students are classified as either successful or not-successful in their graduate studies.The officer has data on 20 current students,ten of whom are doing very well Group 1)and ten who are not Group 2).
   Unpooled Estimates of within-group Covariance matrices are used,assuming they are different.
Group Centroids
Group Quantitative Verbal
1 683.8 654.2
2 610.7 605.7
 $\text { Classitication Matrix }$
$\begin{array}{cccc} 
\text { Actual / Predicted }
& \text { Group1 } & \text { Group2 } & \text { Total } & \% \text { correct } \
\hline \text { Group1 } & 9 & 1 & 1 & 90.00 \% \
&& & 0 & \
\text { Group2 }&  2 &8 & 1 & 80.00 \% \
&  &  & 0 & \\
\text { Total } & 1 & 9& 2 & 85.00 \%\
&1&&0 
\end{array}$ 
-Refer to Exhibit 10.1.What number of observations is classified incorrectly?

Accepted Answer

A)  3
B)  9
C)  17
D)  20

Question 16

Oversampling forces a classification method to

Accepted Answer

A)  discriminate between groups
B)  classifying records correctly
C)  classifying records incorrectly
D)  perform a large number of iterations

Question 17

Exhibit 10.1
The following questions are based on the problem description,regression results,and the Analytic Solver Platform Discriminant Analysis report below.
A college admissions officer wants to evaluate graduate school applicants based on their GMAT scores,verbal and quantitative.Students are classified as either successful or not-successful in their graduate studies.The officer has data on 20 current students,ten of whom are doing very well Group 1)and ten who are not Group 2).
   Unpooled Estimates of within-group Covariance matrices are used,assuming they are different.
Group Centroids
Group Quantitative Verbal
1 683.8 654.2
2 610.7 605.7
 $\text { Classitication Matrix }$
$\begin{array}{cccc} 
\text { Actual / Predicted }
& \text { Group1 } & \text { Group2 } & \text { Total } & \% \text { correct } \
\hline \text { Group1 } & 9 & 1 & 1 & 90.00 \% \
&& & 0 & \
\text { Group2 }&  2 &8 & 1 & 80.00 \% \
&  &  & 0 & \\
\text { Total } & 1 & 9& 2 & 85.00 \%\
&1&&0 
\end{array}$ 
-Refer to Exhibit 10.1.What is the straight line distance between 6,4)and 2,9)?

Accepted Answer

A)  3.20
B)  6.40
C)  9
D)  41

Question 18

Logistic regression is a classification technique that

Accepted Answer

A)  outperforms other techniques acros a variety of data collections
B)  is not reliable
C)  is not robust
D)  is not feasible for most data sets

Question 19

Exhibit 10.2
The following questions are based on the problem description,spreadsheet,and the Analytic Solver Platform Discriminant Analysis report below.
A college admissions officer wants to evaluate graduate school applicants based on their GMAT scores,verbal and quantitative.Students are classified as either successful Group 1),marginally successful Group 2)or not- successful Group 3)in their graduate studies.The officer has data on 20 current students,7 successful Group 1),6 marginally successful Group 2)and 7 not successful Group 3).
  Discriminant Analysis Report
October 1,2013 4:22:38 PM
Unpooled Estimates of within-group Covariance matrices are used,assuming they are different.
 $\begin{array}{lll}
\text {Group}\
\text { Centroids}\
\text { Group } & \text { Quantitative } & \text { Verbal } \
\hline 1 & 697.7142857 & 650.4285714 \
2 & 647.8571429 & 630.7142857 \
3 & 5876666667 & 6051666667
\end{array}$
 $\text {Group}$
$\text {Frenuencies}$
$\begin{array}{cr}
\text { Group } & \begin{array}{r}
\text { Relative } \
\text { Frequency }
\end{array} \
\hline 1 & 35.00 \% \
2 & 35.00 \% \
3 & 30.00\%
\end{array}$
 Training Sample Classification
Mahalanobis Distances
  $\text {Classification}$
$\text {Matrix}$
$\begin{array}{llllll}
\text { Actual / Predicted } & \text { Group1 } & \text { Group2 } & \text { Group3 } & \text { Total } & \% \text { correct } \
\hline \text { Group1 } & 6 & 1 & 0 & 7 & 85.71 \% \
\text { Group2 } & 0 & 7 & 0 & 7 & 100.00 \% \
\text { Group3 } & 0 & 0 & 6 & 6 & 100.00 \% \
\text { Total } & 6 & 8 & 6 & 2 & 95.00 \%
\end{array}$

-Refer to Exhibit 10.2.What is the verbal test score value of the group centroid for group 3?

Accepted Answer

A)  697.71
B)  647.86
C)  587.67
D)  605.17

Question 20

In hierarchical clustering,the measure of similarity between clusters is/are

Accepted Answer

A)  single linkage
B)  complete linkage
C)  Ward's method
D)  all of the above

Exam 10: Data Mining