Data Mining And Warehouse Set 5 MCQs

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.