Question 1

Supervised learning and unsupervised clustering both require at least one

Accepted Answer

A)  hidden attribute. 
B)  output attribute. 
C)  input attribute. 
D)  categorical attribute. 
A)  hidden attribute. 
B)  output attribute. 
C)  input attribute. 
D)  categorical attribute. C

Question 2

Which of the following is a valid production rule for the decision tree below?

Accepted Answer

A)  IF Business Appointment = No & Temp above 70 = No THEN Decision = wear slacks 
B)  IF Business Appointment = Yes & Temp above 70 = Yes THEN Decision = wear shorts 
C)  IF Temp above 70 = No THEN Decision = wear shorts 
D)  IF Business Appointment= No & Temp above 70 = No THEN Decision = wear jeans 
A)  IF Business Appointment = No & Temp above 70 = No THEN Decision = wear slacks 
B)  IF Business Appointment = Yes & Temp above 70 = Yes THEN Decision = wear shorts 
C)  IF Temp above 70 = No THEN Decision = wear shorts 
D)  IF Business Appointment= No & Temp above 70 = No THEN Decision = wear jeans D

Question 3

Determine which is the best approach for each problem.
-Develop a profile for credit card customers likely to carry an average monthly balance of more than $1000.00.

Accepted Answer

A) supervised learning 
B) unsupervised clustering 
C) data query 
A) supervised learning 
B) unsupervised clustering 
C) data query A

Question 4

Determine which is the best approach for each problem.
-Determine whether a credit card transaction is valid or fraudulent.

Accepted Answer

A) supervised learning 
B) unsupervised clustering 
C) data query 
A) supervised learning 
B) unsupervised clustering 
C) data query

Question 5

Determine which is the best approach for each problem.
-What attribute similarities group customers holding one or several insurance policies?

Accepted Answer

A) supervised learning 
B) unsupervised clustering 
C) data query 
A) supervised learning 
B) unsupervised clustering 
C) data query

Question 6

A person trained to interact with a human expert in order to capture their knowledge.

Accepted Answer

A)  knowledge programmer 
B)  knowledge developer 
C)  knowledge engineer 
D)  knowledge extractor 
A)  knowledge programmer 
B)  knowledge developer 
C)  knowledge engineer 
D)  knowledge extractor

Question 7

A structure designed to store data for decision support.

Accepted Answer

A)  operational database 
B)  flat file 
C)  decision tree 
D)  data warehouse 
A)  operational database 
B)  flat file 
C)  decision tree 
D)  data warehouse

Question 8

A nearest neighbor approach is best used

Accepted Answer

A)  with large-sized datasets. 
B)  when irrelevant attributes have been removed from the data. 
C)  when a generalized model of the data is desireable. 
D)  when an explanation of what has been found is of primary importance. 
A)  with large-sized datasets. 
B)  when irrelevant attributes have been removed from the data. 
C)  when a generalized model of the data is desireable. 
D)  when an explanation of what has been found is of primary importance.

Question 9

Supervised learning differs from unsupervised clustering in that supervised learning requires

Accepted Answer

A)  at least one input attribute. 
B)  input attriutes to be categorical. 
C)  at least one output attribute. 
D)  ouput attriubutes to be categorical. 
A)  at least one input attribute. 
B)  input attriutes to be categorical. 
C)  at least one output attribute. 
D)  ouput attriubutes to be categorical.

Question 10

A statement to be tested.

Accepted Answer

A)  theory 
B)  procedure 
C)  principle 
D)  hypothesis 
A)  theory 
B)  procedure 
C)  principle 
D)  hypothesis

Question 11

The process of forming general concept definitions from examples of concepts to be learned.

Accepted Answer

A)  deduction 
B)  abduction 
C)  induction 
D)  conjunction 
A)  deduction 
B)  abduction 
C)  induction 
D)  conjunction

Question 12

Data used to build a data mining model.

Accepted Answer

A)  validation data 
B)  training data 
C)  test data 
D)  hidden data 
A)  validation data 
B)  training data 
C)  test data 
D)  hidden data

Question 13

Which of the following is not a characteristic of a data warehouse?

Accepted Answer

A)  contains historical data 
B)  designed for decision support 
C)  stores data in normalized tables 
D)  promotes data redundancy 
A)  contains historical data 
B)  designed for decision support 
C)  stores data in normalized tables 
D)  promotes data redundancy

Question 14

If a customer is spending more than expected, the customer's intrinsic value is ________ their actual value.

Accepted Answer

A)  greater than 
B)  less than 
C)  less than or equal to 
D)  equal to Matching Questions 
A)  greater than 
B)  less than 
C)  less than or equal to 
D)  equal to Matching Questions

Question 15

Data mining is best described as the process of

Accepted Answer

A)  identifying patterns in data. 
B)  deducing relationships in data. 
C)  representing data. 
D)  simulating trends in data. 
A)  identifying patterns in data. 
B)  deducing relationships in data. 
C)  representing data. 
D)  simulating trends in data.

Question 16

Determine which is the best approach for each problem.
-Do single men play more golf than married men?

Accepted Answer

A) supervised learning 
B) unsupervised clustering 
C) data query 
A) supervised learning 
B) unsupervised clustering 
C) data query

Question 17

Database query is used to uncover this type of knowledge.

Accepted Answer

A)  deep 
B)  hidden 
C)  shallow 
D)  multidimensional 
A)  deep 
B)  hidden 
C)  shallow 
D)  multidimensional

Question 18

Determine which is the best approach for each problem.
-Determine the characteristics of a successful used car salesperson.

Accepted Answer

A) supervised learning 
B) unsupervised clustering 
C) data query 
A) supervised learning 
B) unsupervised clustering 
C) data query

Question 19

Computers are best at learning

Accepted Answer

A)  facts. 
B)  Concepts. 
C)  Procedures. 
D)  Principles. 
A)  facts. 
B)  Concepts. 
C)  Procedures. 
D)  Principles.

Question 20

Determine which is the best approach for each problem.
-Do meaningful attribute relationships exist in a database containing information about credit card customers?

Accepted Answer

A) supervised learning 
B) unsupervised clustering 
C) data query 
A) supervised learning 
B) unsupervised clustering 
C) data query

Supervised learning and unsupervised clustering both require at least one

Which of the following is a valid production rule for the decision tree below?

Determine which is the best approach for each problem. -Develop a profile for credit card customers likely to carry an average monthly balance of more than $1000.00.

Determine which is the best approach for each problem. -Determine whether a credit card transaction is valid or fraudulent.

Determine which is the best approach for each problem. -What attribute similarities group customers holding one or several insurance policies?

A person trained to interact with a human expert in order to capture their knowledge.

A structure designed to store data for decision support.

A nearest neighbor approach is best used

Supervised learning differs from unsupervised clustering in that supervised learning requires

A statement to be tested.

The process of forming general concept definitions from examples of concepts to be learned.

Data used to build a data mining model.

Which of the following is not a characteristic of a data warehouse?

If a customer is spending more than expected, the customer's intrinsic value is ________ their actual value.

Data mining is best described as the process of

Determine which is the best approach for each problem. -Do single men play more golf than married men?

Database query is used to uncover this type of knowledge.

Determine which is the best approach for each problem. -Determine the characteristics of a successful used car salesperson.

Computers are best at learning

Determine which is the best approach for each problem. -Do meaningful attribute relationships exist in a database containing information about credit card customers?

Data Mining: a Closer Look

Basic Data Mining Techniques

An Excel-Based Data Mining Tool

Knowledge Discovery in Databases

The Data Warehouse

Formal Evaluation Techniques

Neural Networks

Building Neural Networks With Ida

Statistical Techniques

Specialized Techniques

Rule-Based Systems

Managing Uncertainty in Rule-Based Systems

Intelligent Agents

Filters

Exam 1: Data Mining: a First View

Supervised learning and unsupervised clustering both require at least one

Which of the following is a valid production rule for the decision tree below?

Determine which is the best approach for each problem. -Develop a profile for credit card customers likely to carry an average monthly balance of more than $1000.00.

Determine which is the best approach for each problem. -Determine whether a credit card transaction is valid or fraudulent.

Determine which is the best approach for each problem. -What attribute similarities group customers holding one or several insurance policies?

A person trained to interact with a human expert in order to capture their knowledge.

A structure designed to store data for decision support.

A nearest neighbor approach is best used

Supervised learning differs from unsupervised clustering in that supervised learning requires

A statement to be tested.

The process of forming general concept definitions from examples of concepts to be learned.

Data used to build a data mining model.

Which of the following is not a characteristic of a data warehouse?

If a customer is spending more than expected, the customer's intrinsic value is ________ their actual value.

Data mining is best described as the process of

Determine which is the best approach for each problem. -Do single men play more golf than married men?

Database query is used to uncover this type of knowledge.

Determine which is the best approach for each problem. -Determine the characteristics of a successful used car salesperson.

Computers are best at learning

Determine which is the best approach for each problem. -Do meaningful attribute relationships exist in a database containing information about credit card customers?

Data Mining: a Closer Look

Basic Data Mining Techniques

An Excel-Based Data Mining Tool

Knowledge Discovery in Databases

The Data Warehouse

Formal Evaluation Techniques

Neural Networks

Building Neural Networks With Ida

Statistical Techniques

Specialized Techniques

Rule-Based Systems

Managing Uncertainty in Rule-Based Systems

Intelligent Agents

Filters