Top 250+ Solved Data Mining and Business Intelligence MCQ Questions Answer

From 151 to 165 of 248

Q. ______ are needed to identify training data and desired results.

a. Programmers

b. Designers

c. Users

d. Administrators

  • c. Users

Q. Over fitting occurs when a model_________.

a. Does fit in future states

b. Does not fit in future states

c. Does fit in current state

d. Does not fit in current state

  • b. Does not fit in future states

Q. The problem of dimensionality curse involves___________.

a. The use of some attributes may interfere with the correct completion of a data mining task.

b. The use of some attributes may simply increase the overall complexity.

c. Some may decrease the efficiency of the algorithm.

d. All of the above

  • d. All of the above

Q. Incorrect or invalid data is known as _______.

a. Changing data

b. Noisy data

c. Outliers

d. Missing data

  • b. Noisy data

Q. ROI is an acronym of _______.

a. Return on Investment

b. Return on Information

c. Repetition of Information

d. Runtime of Instruction

  • a. Return on Investment

Q. The ______of data could result in the disclosure of information that is deemed to beconfidential.

a. Authorized use

b. Unauthorized use

c. Authenticated use

d. Unauthenticated use

  • b. Unauthorized use

Q. _________data are noisy and have many missing attribute values.

a. Preprocessed

b. Cleaned

c. Real-worl

d. D Tr

  • d. D Tr

Q. The rise of DBMS occurred in early _______.

a. 1950's

b. 1960's

c. 1970's

d. 1980's

  • c. 1970's

Q. SQL stand for_________.

a. Standard Query Language

b. Structured Query Language

c. Standard Quick List.

d. Structured Query list

  • b. Structured Query Language

Q. Which of the following is not a data mining metric?

a. Space complexity

b. Time complexity

c. ROI

d. All of the above

  • d. All of the above

Q. Reducing the number of attributes to solve the high dimensionality problem is calledas_____________.

a. Dimensionality curse

b. Dimensionality reduction

c. Cleaning

d. Over fitting

  • b. Dimensionality reduction

Q. Data that are not of interest to the data mining task is called as _____.

a. Missing data

b. Changing data

c. Irrelevant data

d. Noisy data

  • c. Irrelevant data

Q. _________are effective tools to attack the scalability problem.

a. Sampling

b. Parallelization

c. Both A & B

d. None of the above

  • c. Both A & B

Q. Market-basket problem was formulated by____________.

a. Agrawal et al

b. Steve et al

c. Toda et al

d. Simon et al

  • a. Agrawal et al

Q. Data mining helps in________.

a. Inventory managemen

b. Sales promotion strategies

c. Marketing strategies

d. All of the above

  • d. All of the above
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