Data Mining And Warehouse Set 8
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This set of Data Mining and Data Warehouse Multiple Choice Questions & Answers (MCQs) focuses on Data Mining And Warehouse Set 8
Q1 | The goal of _____ is to discover both the dense and sparse regions of a data set.
- association rule.
- classification.
- clustering.
- genetic algorithm.
Q2 | Which of the following is a clustering algorithm?
- a priori.
- clara.
- pincer-search.
- fp-growth.
Q3 | _______ clustering technique start with as many clusters as there are records, with each cluster havingonly one record.
- agglomerative.
- divisive.
- partition.
- numeric.
Q4 | __________ clustering techniques starts with all records in one cluster and then try to split that clusterinto small pieces.
- agglomerative.
- divisive.
- partition.
- numeric.
Q5 | Which of the following is a data set in the popular UCI machine-learning repository?
- clara.
- cactus.
- stirr.
- mushroom.
Q6 | In ________ algorithm each cluster is represented by the center of gravity of the cluster.
- k-medoid.
- k-means.
- stirr.
- rock.
Q7 | In ___________ each cluster is represented by one of the objects of the cluster located near thecenter.
- k-medoid.
- k-means.
- stirr.
- rock.
Q8 | Pick out a k-medoid algoithm.
- dbscan.
- birch.
- pam.
- cure.
Q9 | Pick out a hierarchical clustering algorithm.
- dbscan
- birch.
- pam.
- cure.
Q10 | CLARANS stands for _______.
- clara net server.
- clustering large application range network search.
- clustering large applications based on randomized search.
- clustering application randomized search.
Q11 | BIRCH is a ________.
- agglomerative clustering algorithm.
- hierarchical algorithm.
- hierarchical-agglomerative algorithm.
- divisive.
Q12 | The cluster features of different subclusters are maintained in a tree called ___________.
- cf tree.
- fp tree.
- fp growth tree.
- b tree.
Q13 | The ________ algorithm is based on the observation that the frequent sets are normally very few innumber compared to the set of all itemsets.
- a priori.
- clustering.
- association rule.
- partition.
Q14 | The partition algorithm uses _______ scans of the databases to discover all frequent sets.
- two.
- four.
- six.
- eight.
Q15 | The basic idea of the apriori algorithm is to generate________ item sets of a particular size & scansthe database.
- candidate.
- primary.
- secondary.
- superkey.
Q16 | An algorithm called________is used to generate the candidate item sets for each pass after the first.
- apriori.
- apriori-gen.
- sampling.
- partition.
Q17 | The basic partition algorithm reduces the number of database scans to ________ & divides it intopartitions.
- one.
- two.
- three.
- four.
Q18 | ___________and prediction may be viewed as types of classification.
- decision.
- verification.
- estimation.
- illustration.
Q19 | ___________can be thought of as classifying an attribute value into one of a set of possible classes.
- estimation.
- prediction.
- identification.
- clarification.
Q20 | Prediction can be viewed as forecasting a_________value.
- non-continuous.
- constant.
- continuous.
- variable.
Q21 | _________data consists of sample input data as well as the classification assignment for the data.
- missing.
- measuring.
- non-training.
- training.
Q22 | Rule based classification algorithms generate ______ rule to perform the classification.
- if-then.
- while.
- do while.
- switch.
Q23 | ____________ are a different paradigm for computing which draws its inspiration from neuroscience.
- computer networks.
- neural networks.
- mobile networks.
- artificial networks.
Q24 | The human brain consists of a network of ___________.
- neurons.
- cells.
- tissue.
- muscles.
Q25 | Each neuron is made up of a number of nerve fibres called _____________.
- electrons.
- molecules.
- atoms.
- dendrites.