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This set of Data Mining and Data Warehouse Multiple Choice Questions & Answers (MCQs) focuses on Data Mining And Warehouse Set 6

Q1 | _____________ helps to uncover hidden information about the data.
  • induction.
  • compression.
  • approximation.
  • summarization.
Q2 | _______ are needed to identify training data and desired results.
  • programmers.
  • designers.
  • users.
  • administrators.
Q3 | Overfitting occurs when a model _________.
  • does fit in future states.
  • does not fit in future states.
  • does fit in current state.
  • does not fit in current state.
Q4 | The problem of dimensionality curse involves ___________.
  • the use of some attributes may interfere with the correct completion of a data mining task.
  • the use of some attributes may simply increase the overall complexity.
  • some may decrease the efficiency of the algorithm.
  • all of the above.
Q5 | Incorrect or invalid data is known as _________.
  • changing data.
  • noisy data.
  • outliers.
  • missing data.
Q6 | ROI is an acronym of ________.
  • return on investment.
  • return on information.
  • repetition of information.
  • runtime of instruction
Q7 | The ____________ of data could result in the disclosure of information that is deemed to beconfidential.
  • authorized use.
  • unauthorized use.
  • authenticated use.
  • unauthenticated use.
Q8 | ___________ data are noisy and have many missing attribute values.
  • preprocessed.
  • cleaned.
  • real-world.
  • transformed.
Q9 | The rise of DBMS occurred in early ___________.
  • 1950\s.
  • 1960\s
  • 1970\s
  • 1980\s.
Q10 | SQL stand for _________.
  • standard query language.
  • structured query language.
  • standard quick list.
  • structured query list.
Q11 | Which of the following is not a data mining metric?
  • space complexity.
  • time complexity.
  • roi.
  • all of the above.
Q12 | Reducing the number of attributes to solve the high dimensionality problem is called as ________.
  • dimensionality curse.
  • dimensionality reduction.
  • cleaning.
  • overfitting.
Q13 | Data that are not of interest to the data mining task is called as ______.
  • missing data.
  • changing data.
  • irrelevant data.
  • noisy data.
Q14 | ______ are effective tools to attack the scalability problem.
  • sampling.
  • parallelization
  • both a & b.
  • none of the above.
Q15 | Market-basket problem was formulated by __________.
  • agrawal et al.
  • steve et al.
  • toda et al.
  • simon et al.
Q16 | Data mining helps in __________.
  • inventory management.
  • sales promotion strategies.
  • marketing strategies.
  • all of the above.
Q17 | The proportion of transaction supporting X in T is called _________.
  • confidence.
  • support.
  • support count.
  • all of the above.
Q18 | The absolute number of transactions supporting X in T is called ___________.
  • confidence.
  • support.
  • support count.
  • none of the above.
Q19 | The value that says that transactions in D that support X also support Y is called ______________.
  • confidence.
  • support.
  • support count.
  • none of the above.
Q20 | If T consist of 500000 transactions, 20000 transaction contain bread, 30000 transaction contain jam,10000 transaction contain both bread and jam. Then the support of bread and jam is _______.
  • 2%
  • 20%
  • 3%
  • 30%
Q21 | 7 If T consist of 500000 transactions, 20000 transaction contain bread, 30000 transaction contain jam,10000 transaction contain both bread and jam. Then the confidence of buying bread with jam is _______.
  • 33.33%
  • 66.66%
  • 45%
  • 50%
Q22 | The left hand side of an association rule is called __________.
  • consequent.
  • onset.
  • antecedent.
  • precedent.
Q23 | The right hand side of an association rule is called _____.
  • consequent.
  • onset.
  • antecedent.
  • precedent.
Q24 | Which of the following is not a desirable feature of any efficient algorithm?
  • to reduce number of input operations.
  • to reduce number of output operations.
  • to be efficient in computing.
  • to have maximal code length.
Q25 | All set of items whose support is greater than the user-specified minimum support are called as_____________.
  • border set.
  • frequent set.
  • maximal frequent set.
  • lattice.