UMKC DSOM- CHP.11: UNSUPERVISED DATA MINING EXAM QUESTIONS AND ANSWERS WITH COMPLETE SOLUTIONS VERIFIED LATEST UPDATE
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DSOM
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DSOM
UMKC DSOM- CHP.11: UNSUPERVISED DATA MINING EXAM QUESTIONS AND ANSWERS WITH COMPLETE SOLUTIONS VERIFIED LATEST UPDATE
Name two popular unsupervised data mining techniques: cluster analysis and association rule analysis.
Multiple select question.
Cluster analysis
Factor analysis
Association...
Name two popular unsupervised data mining techniques: cluster analysis and
association rule analysis.
Multiple select question.
Cluster analysis
Factor analysis
Association rule analysis
Discriminant analysis
Cluster analysis
Association rule analysis
Unsupervised data mining, also referred to as unsupervised learning, requires no
knowledge of the response variable.It is called unsupervised because:(select the
correct response below)
Multiple choice question.
The algorithms allow the computer to identify complex processes and patterns
without any specific guidance from the analyst
, The known values of the response variable are used to build a model in the
training set
These models are used to predict the outcome of an output (response or target)
variable based on several input (predictor) variables
The analyst provides guidance for the computer to identify complex processes
and patterns
The algorithms allow the computer to identify complex processes and patterns without
any specific guidance from the analyst
Hierarchical clustering is a technique that uses an iterative process to group data
into a hierarchy of clusters. What are two common strategies of hierarchical
clustering?
Multiple select question.
Agglomerative clustering
k-means clustering
Divisive clustering
Supervised clustering
Agglomerative clustering
Divisive clustering
In AGNES, each observation in the data initially forms its own cluster. The
algorithm then successively merges these clusters into larger clusters based on
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