Question 1

Which of the following is a commonly used supervised learning method?

Accepted Answer

A) k-means clustering 
B) k-nearest neighbors 
C) hierarchical clustering 
D) association rule development 
A) k-means clustering 
B) k-nearest neighbors 
C) hierarchical clustering 
D) association rule development

Question 2

_____________is the step in data-mining which includes addressing missing and erroneous data, reducing the number of variables, defining new variables, and data exploration.

Accepted Answer

A) Data sampling 
B) Data partitioning 
C) Data preparation 
D) Model assessment 
A) Data sampling 
B) Data partitioning 
C) Data preparation 
D) Model assessment

Question 3

Determine a freshman's likely first-year grade point average from the student's Scholastic Aptitude Test (SAT) score, high school grade point average, and number of extra-curricular activities. This is an example of

Accepted Answer

A) classification of a categorical outcome. 
B) estimation of a continuous outcome. 
C) prediction of a categorical outcome. 
D) unsupervised learning. 
A) classification of a categorical outcome. 
B) estimation of a continuous outcome. 
C) prediction of a categorical outcome. 
D) unsupervised learning.

Question 4

_____ is a measure of the heterogeneity of observations in a classification tree.

Accepted Answer

A) Sensitivity 
B) Specificity 
C) Accuracy 
D) Impurity 
A) Sensitivity 
B) Specificity 
C) Accuracy 
D) Impurity

Question 5

Data used to build a data mining model is called

Accepted Answer

A) validation data. 
B) training data. 
C) test data. 
D) exploration data. 
A) validation data. 
B) training data. 
C) test data. 
D) exploration data.

Question 6

__________is one minus the Class 0 error rate.

Accepted Answer

A) Sensitivity 
B) Specificity 
C) Accuracy 
D) Cutoff value 
A) Sensitivity 
B) Specificity 
C) Accuracy 
D) Cutoff value

Question 7

___________ is dividing the sample data into three sets for training, validation, and testing of the data-mining algorithm performance.

Accepted Answer

A) Data sampling 
B) Data partitioning 
C) Data preparation 
D) Model assessment 
A) Data sampling 
B) Data partitioning 
C) Data preparation 
D) Model assessment

Question 8

As we increase the cutoff value, _______ error will decrease. And_________error will rise.

Accepted Answer

A) Class 0, Class 1 
B) Class 1, Class 0 
C) error, accuracy 
D) false, true 
A) Class 0, Class 1 
B) Class 1, Class 0 
C) error, accuracy 
D) false, true

Question 9

____________is the manipulation of the data with the goal of putting it in a form suitable for formal modeling.

Accepted Answer

A) Data sampling 
B) Data partitioning 
C) Data preparation 
D) Model assessment 
A) Data sampling 
B) Data partitioning 
C) Data preparation 
D) Model assessment

Question 10

In the k-nearest neighbors method, when the value of k is set to 1

Accepted Answer

A) the classification or prediction of a new observation is based solely on the single most similar observation from the training set. 
B) the new observation's class is naïvely assigned to the most common class in the training set. 
C) the new observation's prediction is used to estimate the anticipated error rate on future data over the entire training set. 
D) the classification or prediction of a new observation is subject to the smallest possible classification error. 
A) the classification or prediction of a new observation is based solely on the single most similar observation from the training set. 
B) the new observation's class is naïvely assigned to the most common class in the training set. 
C) the new observation's prediction is used to estimate the anticipated error rate on future data over the entire training set. 
D) the classification or prediction of a new observation is subject to the smallest possible classification error.

Question 11

The Y axis of a decile chart shows

Accepted Answer

A) number of important class records identified. 
B) ratio of decile mean to overall mean. 
C) the number of actual Class 1 records. 
D) the ratio of the overall mean to the decile mean. 
A) number of important class records identified. 
B) ratio of decile mean to overall mean. 
C) the number of actual Class 1 records. 
D) the ratio of the overall mean to the decile mean.

Question 12

The impurity of a group of observations is based on the variance of the outcome value for the observations in the group for

Accepted Answer

A) regression trees. 
B) time-series plots. 
C) classification trees. 
D) cumulative lift charts. 
A) regression trees. 
B) time-series plots. 
C) classification trees. 
D) cumulative lift charts.

Question 13

Classifying a record as belonging to one class when it belongs to another class is referred to as a(n)

Accepted Answer

A) overall error rate. 
B) error. 
C) accuracy. 
D) class. 
A) overall error rate. 
B) error. 
C) accuracy. 
D) class.

Question 14

_______ attempts to classify a categorical outcome as a linear function of explanatory variables.

Accepted Answer

A) Linear regression 
B) Logistic regression 
C) Classification model 
D) Supervised learning 
A) Linear regression 
B) Logistic regression 
C) Classification model 
D) Supervised learning

Question 15

One minus the overall error rate is often referred to as the _____ of the model.

Accepted Answer

A) sensitivity 
B) accuracy 
C) specificity 
D) cutoff value 
A) sensitivity 
B) accuracy 
C) specificity 
D) cutoff value

Question 16

A characteristic or quantity of interest that can take on different values is a(n)

Accepted Answer

A) variable. 
B) observation. 
C) record. 
D) quality. 
A) variable. 
B) observation. 
C) record. 
D) quality.

Question 17

How many Class 1's are correctly classified as Class 1 in the Table below? $$\begin{array} { | l | c | c | } 
\hline  { \text { Classification Confusion Matrix } } \
\hline &  { \text { Predicted Class } } \
\hline \text { Actual Class } & 1 & 0 \
\hline 1 & 221 & 100 \
\hline 0 & 30 & 3,000 \
\hline
\end{array}$$ ?

Accepted Answer

A) 221 
B) 100 
C) 30 
D) 3,000 
A) 221 
B) 100 
C) 30 
D) 3,000

Question 18

How many Class 1's are incorrectly classified as Class 0? $$\begin{array} { | l | c | c | } 
\hline  { \text { Classification Confusion Matrix } } \
\hline &  { \text { Predicted Class } } \
\hline \text { Actual Class } & 1 & 0 \
\hline 1 & 221 & 100 \
\hline 0 & 30 & 3,000 \
\hline
\end{array}$$ ?

Accepted Answer

A) 221 
B) 100 
C) 30 
D) 3,000 
A) 221 
B) 100 
C) 30 
D) 3,000

Question 19

A(n) __________ matrix displays a model's correct and incorrect classification.

Accepted Answer

A) cumulative lift 
B) classification confusion 
C) decile-wise lift chart 
D) ROC curve 
A) cumulative lift 
B) classification confusion 
C) decile-wise lift chart 
D) ROC curve

Question 20

The set of recorded values of variables associated with a single entity is a(n)

Accepted Answer

A) observation. 
B) data point. 
C) classification. 
D) location. 
A) observation. 
B) data point. 
C) classification. 
D) location.

Which of the following is a commonly used supervised learning method?

_____________is the step in data-mining which includes addressing missing and erroneous data, reducing the number of variables, defining new variables, and data exploration.

Determine a freshman's likely first-year grade point average from the student's Scholastic Aptitude Test (SAT) score, high school grade point average, and number of extra-curricular activities. This is an example of

_____ is a measure of the heterogeneity of observations in a classification tree.

Data used to build a data mining model is called

__________is one minus the Class 0 error rate.

___________ is dividing the sample data into three sets for training, validation, and testing of the data-mining algorithm performance.

As we increase the cutoff value, _ error will decrease. And___error will rise.

____________is the manipulation of the data with the goal of putting it in a form suitable for formal modeling.

In the k-nearest neighbors method, when the value of k is set to 1

The Y axis of a decile chart shows

The impurity of a group of observations is based on the variance of the outcome value for the observations in the group for

Classifying a record as belonging to one class when it belongs to another class is referred to as a(n)

_______ attempts to classify a categorical outcome as a linear function of explanatory variables.

One minus the overall error rate is often referred to as the _____ of the model.

A characteristic or quantity of interest that can take on different values is a(n)

How many Class 1's are correctly classified as Class 1 in the Table below? Classification Confusion Matrix Predicted Class Actual Class 1 0 1 221 100 0 30 3,000 ?

How many Class 1's are incorrectly classified as Class 0? Classification Confusion Matrix Predicted Class Actual Class 1 0 1 221 100 0 30 3,000 ?

A(n) __________ matrix displays a model's correct and incorrect classification.

The set of recorded values of variables associated with a single entity is a(n)

Introduction

Descriptive Statistics

Data Visualization

Descriptive Data Mining

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Linear Regression

Time Series Analysis and Forecasting

Spreadsheet Models

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Monte Carlo Simulation

Decision Analysis

Filters

Exam 9: Predictive Data Mining

Which of the following is a commonly used supervised learning method?

_____________is the step in data-mining which includes addressing missing and erroneous data, reducing the number of variables, defining new variables, and data exploration.

Determine a freshman's likely first-year grade point average from the student's Scholastic Aptitude Test (SAT) score, high school grade point average, and number of extra-curricular activities. This is an example of

_____ is a measure of the heterogeneity of observations in a classification tree.

Data used to build a data mining model is called

__________is one minus the Class 0 error rate.

___________ is dividing the sample data into three sets for training, validation, and testing of the data-mining algorithm performance.

As we increase the cutoff value, _______ error will decrease. And_________error will rise.

____________is the manipulation of the data with the goal of putting it in a form suitable for formal modeling.

In the k-nearest neighbors method, when the value of k is set to 1

The Y axis of a decile chart shows

The impurity of a group of observations is based on the variance of the outcome value for the observations in the group for

Classifying a record as belonging to one class when it belongs to another class is referred to as a(n)

_______ attempts to classify a categorical outcome as a linear function of explanatory variables.

One minus the overall error rate is often referred to as the _____ of the model.

A characteristic or quantity of interest that can take on different values is a(n)

How many Class 1's are correctly classified as Class 1 in the Table below? Classification Confusion Matrix Predicted Class Actual Class 1 0 1 221 100 0 30 3,000 ?

How many Class 1's are incorrectly classified as Class 0? Classification Confusion Matrix Predicted Class Actual Class 1 0 1 221 100 0 30 3,000 ?

A(n) __________ matrix displays a model's correct and incorrect classification.

The set of recorded values of variables associated with a single entity is a(n)

Introduction

Descriptive Statistics

Data Visualization

Descriptive Data Mining

Probability: an Introduction to Modeling Uncertainty

Statistical Inference

Linear Regression

Time Series Analysis and Forecasting

Spreadsheet Models

Linear Optimization Models

Integer Linear Optimization Models

Nonlinear Optimization Models

Monte Carlo Simulation

Decision Analysis

Filters

As we increase the cutoff value, _ error will decrease. And___error will rise.