Question 1

The chart below is a summary of the main results of a test data set representing the population observed purchasing a virtual digital assistant. What does the accuracy rate indicate?

Accepted Answer

A)   88.5% of the population has purchased a virtual assistant.
B)   90% of the observations are correctly classified.
C)   88.5% of the observations are correctly classified.
D)   11.5% of the observations are correctly classified. C

Question 2

For a new observation of (0, 0, 0), what is the k-nearest neighbor when k = 1.

Accepted Answer

A)   1, 1, 1
B)   -2, -1, 0
C)   0, 1, 3
D)   -1, 0, 1 D

Question 3

An issue with the naïve Bayes classifier is determining rare outcomes because the estimate is 0. To overcome this problem, the algorithm allows a replacement of zero probability with a nonzero value. This technique is called

Accepted Answer

A)   replacement.
B)   smoothing.
C)   discrete.
D)   combinations. B

Question 4

What is the Euclidean distance between Observation 2 and the origin point of (0, 0, 0)?

Accepted Answer

A)   0
B)   2
C)   5
D)   3

Question 5

A new applicant, age 45, is applying for a loan. Using the table below, what is the estimated probability the loan will be approved? k = 4.

Accepted Answer

A)   The probable default rate is 50%, the loan will be declined.
B)   The probable success rate is 50%, the loan will be approved.
C)   The probable success rate is 30%, the loan will be approved.
D)   The probable default rate is 25%, the loan will be declined.

Question 6

Of the following options, which does not represent the naïve Bayes method?

Accepted Answer

A)   All predictor variables are categorical.
B)   All predictor variables are independent.
C)   Does not capture possible interactions between predictor variables.
D)   Works best on a small data set.

Question 7

A new applicant, age 32, is applying for a loan. Using the table below, what is the estimated probability the loan will default using k = 3.

Accepted Answer

A)   100%
B)   66%
C)   33%
D)   0%

Question 8

In a decile-wise lift chart, what does the lift value of the leftmost bar imply?

Accepted Answer

A)   The lift value is determined by the smoothing of the data.
B)   The first 10% yields twice as many as a random selection of 10% would.
C)   The bar represents 10% of the data cumulative score.
D)   The first 10% is twice as prevalent as 20%.

Question 9

What is the Euclidean distance between Observation 1 and the origin point of (0, 0, 0)?

Accepted Answer

A)   3
B)   1
C)   0
D)   2

Question 10

The chart below is a summary of the main results of a test data set representing the population observed purchasing a virtual digital assistant. What is the percent of the results that are incorrectly classified?

Accepted Answer

A)   11%
B)   8%
C)   12.05%
D)   10.70%

Question 11

An R's ROC curve with AUC = 0.9453 is presented below from an analysis on potential increased membership level from current basic members at Costco Wholesale. What does the AUC indicate on the prediction on increased membership enrollment among current base members?

Accepted Answer

A)   The high AUC indicates an anomaly in that it requires data smoothing to match the baseline.
B)   The high AUC indicates the KNN model performs well and better than the baseline model.
C)   The high AUC indicates the KNN model is not predicting the level increase based on the baseline model.
D)   The high AUC indicates there is a 0.05% probability the KNN model performs as predicted.

Question 12

Marta is partitioning her data set into 60% for training and 40% for validation. She is first specifying 'Member' as her target variable. What will she need to program to ensure consistency to fix a random seed?

Accepted Answer

A)   myIndex
B)   trainSet
C)   createDataPartition
D)   set.seed

Question 13

If the performance measures from the training data are considerably higher than the values from the validation and test data, what could be the issue?

Accepted Answer

A)   Proportion
B)   Sensitivity
C)   Duplication
D)   Overfitting

Question 14

To validate the model on the validation set, Mary calibrates the output of the model to examining all possible outcomes of the prediction (true positive, true negative, false positive, false negative). One way is to use a cutoff value and use functions such as the ifelse () function. These statements are called

Accepted Answer

A)   prediction.
B)   set.seed.
C)   reference.
D)   confusionMatrix.

Question 15

Naïve Bayes classifiers are relatively simple, efficient, and assume dependency among predictors.

Accepted Answer

A) True 
 B)False

Question 16

This chart determines how well the model performs in terms of sensitivity and specificity.

Accepted Answer

A)   Decile-wise chart
B)   Cumulative lift chart
C)   Scatterplot
D)   ROC Curve

Question 17

The chart below is a summary of the main results of a test data set representing the population observed purchasing a virtual digital assistant. What does the accuracy rate indicate?

Accepted Answer

A)   85.6% of the population has purchased a virtual assistant.
B)   60% of the observations are correctly classified.
C)   85.6% of the observations are correctly classified.
D)   14.4% of the observations are correctly classified.

Question 18

Mark is reviewing a partial summary of results from a test data set on a small health clinic. With an accuracy 75% (100 count), Sensitivity 50%, and Specificity 100%, can Mark correctly predict the true positive rate to identify those with the flu?

Accepted Answer

A)   Yes, because the specificity is 100% identifying healthy patients.
B)   No, because the test set identified all patients with the flu.
C)   No, because the sensitivity rate is only 50% in identifying those with the flu.
D)   Yes, because there is a 75% accuracy rate with all healthy identified.

Question 19

Using the following table, what is the estimate of P(Color) = Black and what is the smoothed estimate of P(Color). k = 1.

Accepted Answer

A)   P(Color = Black)  = 0.30 and Smoothed 0.471
B)   P(Color = Black)  = 0.30 and Smoothed 0.380
C)   P(Color = Black)  = 0.7 and Smoothed 0.471
D)   P(Color = Black)  = 0.40 and Smoothed 0.471

Question 20

Using the following table, which k should be used in the subsequent calculations?

Accepted Answer

A)   8
B)   5
C)   6
D)   None of the percentages should be used.

Exam 9: Supervised Data Mining: K-Nearest Neighbors and Naãve Bayes

The chart below is a summary of the main results of a test data set representing the population observed purchasing a virtual digital assistant. What does the accuracy rate indicate?

For a new observation of (0, 0, 0) , what is the k-nearest neighbor when k = 1.

An issue with the naïve Bayes classifier is determining rare outcomes because the estimate is 0. To overcome this problem, the algorithm allows a replacement of zero probability with a nonzero value. This technique is called

What is the Euclidean distance between Observation 2 and the origin point of (0, 0, 0) ?

A new applicant, age 45, is applying for a loan. Using the table below, what is the estimated probability the loan will be approved? k = 4.

Of the following options, which does not represent the naïve Bayes method?

A new applicant, age 32, is applying for a loan. Using the table below, what is the estimated probability the loan will default using k = 3.

In a decile-wise lift chart, what does the lift value of the leftmost bar imply?

What is the Euclidean distance between Observation 1 and the origin point of (0, 0, 0) ?

The chart below is a summary of the main results of a test data set representing the population observed purchasing a virtual digital assistant. What is the percent of the results that are incorrectly classified?

An R's ROC curve with AUC = 0.9453 is presented below from an analysis on potential increased membership level from current basic members at Costco Wholesale. What does the AUC indicate on the prediction on increased membership enrollment among current base members?

Marta is partitioning her data set into 60% for training and 40% for validation. She is first specifying 'Member' as her target variable. What will she need to program to ensure consistency to fix a random seed?

If the performance measures from the training data are considerably higher than the values from the validation and test data, what could be the issue?

Naïve Bayes classifiers are relatively simple, efficient, and assume dependency among predictors.

This chart determines how well the model performs in terms of sensitivity and specificity.

The chart below is a summary of the main results of a test data set representing the population observed purchasing a virtual digital assistant. What does the accuracy rate indicate?

Mark is reviewing a partial summary of results from a test data set on a small health clinic. With an accuracy 75% (100 count) , Sensitivity 50%, and Specificity 100%, can Mark correctly predict the true positive rate to identify those with the flu?

Using the following table, what is the estimate of P(Color) = Black and what is the smoothed estimate of P(Color) . k = 1.

Using the following table, which k should be used in the subsequent calculations?