Introduction to Data Mining, 2nd Edition (Global Edition)
by Pang-Ning Tan, Michael Steinbach, Vipin
Kumar ;eText ISBN:9780134080284 published
by Pearson Copyright© 2019 Test Bank -
,
,Chapter: Chapter 01 - Introduction
Multiple Choice
1. Which statement best describes data mining tasks in data mining?
A) data mining tasks is unrelated to knowledge discovery
B) data mining tasks is a core concept for understanding Introduction and involves appropriate
algorithms and evaluationC) data mining tasks only applies to small datasets
D) data mining tasks replaces all data preprocessing steps
Ans: B
Ahead: data mining tasks
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
Explanation: In Tan et al., data mining tasks is central to Introduction. It defines how data is analyzed, models are
built, and patterns are evaluated.
Option B correctly captures its role in algorithm selection, interpretation, and performance, while other options
are inaccurate.
2. Which statement best describes KDD process in data mining?
A) KDD process is unrelated to knowledge discovery
B) KDD process is a core concept for understanding Introduction and involves appropriate
algorithms and evaluationC) KDD process only applies to small datasets
D) KDD process replaces all data preprocessing steps
Ans: B
Ahead: KDD process
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
Explanation: In Tan et al., KDD process is central to Introduction. It defines how data is analyzed, models are
built, and patterns are evaluated.
Option B correctly captures its role in algorithm selection, interpretation, and performance, while other options
are inaccurate.
3. Which statement best describes data mining vs query in data mining?
A) data mining vs query is unrelated to knowledge discovery
B) data mining vs query is a core concept for understanding Introduction and involves appropriate
algorithms and evaluationC) data mining vs query only applies to small datasets
D) data mining vs query replaces all data preprocessing steps
Ans: B
Ahead: data mining vs query
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
, Explanation: In Tan et al., data mining vs query is central to Introduction. It defines how data is analyzed, models
are built, and patterns are evaluated. Option B correctly captures its role in algorithm selection, interpretation,
and performance, while other options are inaccurate.
4. Which statement best describes predictive vs descriptive in data mining?
A) predictive vs descriptive is unrelated to knowledge discovery
B) predictive vs descriptive is a core concept for understanding Introduction and involves appropriate
algorithms andevaluation
C) predictive vs descriptive only applies to small datasets
D) predictive vs descriptive replaces all data preprocessing steps
Ans: B
Ahead: predictive vs descriptive
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
Explanation: In Tan et al., predictive vs descriptive is central to Introduction. It defines how data is analyzed,
models are built, and patterns are evaluated. Option B correctly captures its role in algorithm selection,
interpretation, and performance, while other options are inaccurate.
5. Which statement best describes applications of data mining in data mining?
A) applications of data mining is unrelated to knowledge discovery
B) applications of data mining is a core concept for understanding Introduction and involves
appropriate algorithms andevaluation
C) applications of data mining only applies to small datasets
D) applications of data mining replaces all data preprocessing steps
Ans: B
Ahead: applications of data mining
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
Explanation: In Tan et al., applications of data mining is central to Introduction. It defines how data is analyzed,
models are built, and patterns are evaluated. Option B correctly captures its role in algorithm selection,
interpretation, and performance, while other options are inaccurate.
6. Which statement best describes data mining tasks in data mining?
A) data mining tasks is unrelated to knowledge discovery
B) data mining tasks is a core concept for understanding Introduction and involves appropriate
algorithms and evaluationC) data mining tasks only applies to small datasets
D) data mining tasks replaces all data preprocessing steps
Ans: B
Ahead: data mining tasks
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
by Pang-Ning Tan, Michael Steinbach, Vipin
Kumar ;eText ISBN:9780134080284 published
by Pearson Copyright© 2019 Test Bank -
,
,Chapter: Chapter 01 - Introduction
Multiple Choice
1. Which statement best describes data mining tasks in data mining?
A) data mining tasks is unrelated to knowledge discovery
B) data mining tasks is a core concept for understanding Introduction and involves appropriate
algorithms and evaluationC) data mining tasks only applies to small datasets
D) data mining tasks replaces all data preprocessing steps
Ans: B
Ahead: data mining tasks
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
Explanation: In Tan et al., data mining tasks is central to Introduction. It defines how data is analyzed, models are
built, and patterns are evaluated.
Option B correctly captures its role in algorithm selection, interpretation, and performance, while other options
are inaccurate.
2. Which statement best describes KDD process in data mining?
A) KDD process is unrelated to knowledge discovery
B) KDD process is a core concept for understanding Introduction and involves appropriate
algorithms and evaluationC) KDD process only applies to small datasets
D) KDD process replaces all data preprocessing steps
Ans: B
Ahead: KDD process
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
Explanation: In Tan et al., KDD process is central to Introduction. It defines how data is analyzed, models are
built, and patterns are evaluated.
Option B correctly captures its role in algorithm selection, interpretation, and performance, while other options
are inaccurate.
3. Which statement best describes data mining vs query in data mining?
A) data mining vs query is unrelated to knowledge discovery
B) data mining vs query is a core concept for understanding Introduction and involves appropriate
algorithms and evaluationC) data mining vs query only applies to small datasets
D) data mining vs query replaces all data preprocessing steps
Ans: B
Ahead: data mining vs query
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
, Explanation: In Tan et al., data mining vs query is central to Introduction. It defines how data is analyzed, models
are built, and patterns are evaluated. Option B correctly captures its role in algorithm selection, interpretation,
and performance, while other options are inaccurate.
4. Which statement best describes predictive vs descriptive in data mining?
A) predictive vs descriptive is unrelated to knowledge discovery
B) predictive vs descriptive is a core concept for understanding Introduction and involves appropriate
algorithms andevaluation
C) predictive vs descriptive only applies to small datasets
D) predictive vs descriptive replaces all data preprocessing steps
Ans: B
Ahead: predictive vs descriptive
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
Explanation: In Tan et al., predictive vs descriptive is central to Introduction. It defines how data is analyzed,
models are built, and patterns are evaluated. Option B correctly captures its role in algorithm selection,
interpretation, and performance, while other options are inaccurate.
5. Which statement best describes applications of data mining in data mining?
A) applications of data mining is unrelated to knowledge discovery
B) applications of data mining is a core concept for understanding Introduction and involves
appropriate algorithms andevaluation
C) applications of data mining only applies to small datasets
D) applications of data mining replaces all data preprocessing steps
Ans: B
Ahead: applications of data mining
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
Explanation: In Tan et al., applications of data mining is central to Introduction. It defines how data is analyzed,
models are built, and patterns are evaluated. Option B correctly captures its role in algorithm selection,
interpretation, and performance, while other options are inaccurate.
6. Which statement best describes data mining tasks in data mining?
A) data mining tasks is unrelated to knowledge discovery
B) data mining tasks is a core concept for understanding Introduction and involves appropriate
algorithms and evaluationC) data mining tasks only applies to small datasets
D) data mining tasks replaces all data preprocessing steps
Ans: B
Ahead: data mining tasks
Complexity: Moderate
Subject: Chapter 1
Taxonomy: Application
Title: Introduction
