Data Mining And Warehouse Set 11
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This set of Data Mining and Data Warehouse Multiple Choice Questions & Answers (MCQs) focuses on Data Mining And Warehouse Set 11
Q1 | Data redundancy between the environments results in less than ____________percent.
- one.
- two.
- three.
- four.
Q2 | Bill Inmon has estimated___________of the time required to build a data warehouse, is consumedin the conversion process.
- 10 percent.
- 20 percent.
- 40 percent
- 80 percent.
Q3 | The biggest drawback of the level indicator in the classic star-schema is that it limits_________
- quantify.
- qualify.
- flexibility.
- ability.
Q4 | Maintenance of cache consistency is the limitation of __________________.
- numa.
- unam.
- mpp.
- pmp.
Q5 | ___________ of data means that the attributes within a given entity are fully dependent on theentire primary key of the entity.
- additivity.
- granularity.
- functional dependency.
- dimensionality.
Q6 | Non-additive measures can often combined with additive measures to create new _________..
- additive measures.
- non-additive measures.
- partially additive.
- all of the above.
Q7 | ____________ of data means that the attributes within a given entity are fully dependent on theentire primary key of the entity.
- additivity.
- granularity.
- functional dependency.
- dependency.
Q8 | _____________ helps to uncover hidden information about the data..
- induction.
- compression.
- approximation.
- summarization.
Q9 | If T consist of 500000 transactions, 20000 transaction contain bread, 30000 transaction containjam, 10000 transaction contain both bread and jam. Then the support of bread and jam is _______.
- 2%
- 20%
- 3%
- 30%
Q10 | 7 If T consist of 500000 transactions, 20000 transaction contain bread, 30000 transaction containjam, 10000 transaction contain both bread and jam. Then the confidence of buying bread with jam is_______.
- 33.33%
- 66.66%
- 45%
- 50%
Q11 | The _______ step eliminates the extensions of (k-1)-itemsets which are not found to be frequent,from being considered for counting support.
- candidate generation.
- pruning.
- partitioning.
- itemset eliminations.
Q12 | The transformed prefix paths of a node 'a' form a truncated database of pattern which co-occurwith a is called _______.
- suffix path.
- fp-tree.
- conditional pattern base.
- prefix path.
Q13 | __________ clustering techniques starts with all records in one cluster and then try to split thatcluster into small pieces.
- agglomerative.
- divisive.
- partition.
- numeric.
Q14 | BIRCH is a ________..
- agglomerative clustering algorithm.
- hierarchical algorithm.
- hierarchical-agglomerative algorithm.
- divisive.
Q15 | The ________ algorithm is based on the observation that the frequent sets are normally very fewin number compared to the set of all itemsets.
- a priori.
- clustering.
- association rule.
- partition.
Q16 | The basic idea of the apriori algorithm is to generate________ item sets of a particular size &scans the database.
- candidate.
- primary.
- secondary.
- superkey.
Q17 | ________is the most well known association rule algorithm and is used in most commercialproducts.
- apriori algorithm.
- partition algorithm.
- distributed algorithm.
- pincer-search algorithm.
Q18 | An algorithm called________is used to generate the candidate item sets for each pass after thefirst.
- apriori.
- apriori-gen.
- sampling.
- partition.
Q19 | ___________can be thought of as classifying an attribute value into one of a set of possibleclasses.
- estimation.
- prediction.
- identification.
- clarification.
Q20 | ____________ are a different paradigm for computing which draws its inspiration fromneuroscience.
- computer networks.
- neural networks.
- mobile networks.
- artificial networks.
Q21 | In a feed- forward networks, the conncetions between layers are ___________ from input tooutput.
- bidirectional.
- unidirectional.
- multidirectional.
- directional.
Q22 | ___________ training may be used when a clear link between input data sets and target outputvalues does not exist.
- competitive.
- perception.
- supervised.
- unsupervised.
Q23 | Investment analysis used in neural networks is to predict the movement of _________ fromprevious data.
- engines.
- stock.
- patterns.
- models.
Q24 | SOMs are used to cluster a specific _____________ dataset containing information about thepatient's drugs etc.
- physical.
- logical.
- medical.
- technical.
Q25 | _______ is concerned with discovering the model underlying the link structures of the web..
- web content mining.
- web structure mining.
- web usage mining.
- all of the above.