Data Mining And Warehouse Set 5
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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.