On This Page

This set of Data Mining and Data Warehouse Multiple Choice Questions & Answers (MCQs) focuses on Data Mining And Warehouse Set 5

Q1 | A fact is said to be partially additive if ___________.
  • it is additive over every dimension of its dimensionality.
  • additive over atleast one but not all of the dimensions.
  • not additive over any dimension.
  • none of the above.
Q2 | A fact is said to be non-additive if ___________.
  • it is additive over every dimension of its dimensionality.
  • additive over atleast one but not all of the dimensions.
  • not additive over any dimension.
  • none of the above.
Q3 | Non-additive measures can often combined with additive measures to create new _________.
  • additive measures.
  • non-additive measures.
  • partially additive.
  • all of the above.
Q4 | A fact representing cumulative sales units over a day at a store for a product is a _________.
  • additive fact.
  • fully additive fact.
  • partially additive fact.
  • non-additive fact.
Q5 | ____________ of data means that the attributes within a given entity are fully dependent on the entireprimary key of the entity.
  • additivity.
  • granularity.
  • functional dependency.
  • dependency.
Q6 | Which of the following is the other name of Data mining?
  • exploratory data analysis.
  • data driven discovery.
  • deductive learning.
  • all of the above.
Q7 | Which of the following is a predictive model?
  • clustering.
  • regression.
  • summarization.
  • association rules.
Q8 | Which of the following is a descriptive model?
  • classification.
  • regression.
  • sequence discovery.
  • association rules.
Q9 | A ___________ model identifies patterns or relationships.
  • descriptive.
  • predictive.
  • regression.
  • time series analysis.
Q10 | A predictive model makes use of ________.
  • current data.
  • historical data.
  • both current and historical data.
  • assumptions.
Q11 | ____________ maps data into predefined groups.
  • regression.
  • time series analysis
  • prediction.
  • classification.
Q12 | __________ is used to map a data item to a real valued prediction variable.
  • regression.
  • time series analysis.
  • prediction.
  • classification.
Q13 | In ____________, the value of an attribute is examined as it varies over time.
  • regression.
  • time series analysis.
  • sequence discovery.
  • prediction.
Q14 | In ________ the groups are not predefined.
  • association rules.
  • summarization.
  • clustering.
  • prediction.
Q15 | Link Analysis is otherwise called as ___________.
  • affinity analysis.
  • association rules.
  • both a & b.
  • prediction.
Q16 | _________ is a the input to KDD.
  • data.
  • information.
  • query.
  • process.
Q17 | The output of KDD is __________.
  • data.
  • information.
  • query.
  • useful information.
Q18 | The KDD process consists of ________ steps.
  • three.
  • four.
  • five.
  • six.
Q19 | Treating incorrect or missing data is called as ___________.
  • selection.
  • preprocessing.
  • transformation.
  • interpretation.
Q20 | Converting data from different sources into a common format for processing is called as ________.
  • selection.
  • preprocessing.
  • transformation.
  • interpretation.
Q21 | Various visualization techniques are used in ___________ step of KDD.
  • selection.
  • transformaion.
  • data mining.
  • interpretation.
Q22 | Extreme values that occur infrequently are called as _________.
  • outliers.
  • rare values.
  • dimensionality reduction.
  • all of the above.
Q23 | Box plot and scatter diagram techniques are _______.
  • graphical.
  • geometric.
  • icon-based.
  • pixel-based.
Q24 | __________ is used to proceed from very specific knowledge to more general information.
  • induction.
  • compression.
  • approximation.
  • substitution.
Q25 | Describing some characteristics of a set of data by a general model is viewed as ____________
  • induction.
  • compression.
  • approximation.
  • summarization.