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DTSA 5505 - Data Mining Methods (Study Cards) EXAM Questions & Answers, Well Elaborated | Already Verified Test |100% Verified solutions |2026 Latest!!

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DTSA 5505 - Data Mining Methods

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6/18/26, 7:35 AM DTSA 5505 - Data Mining Methods (Study Cards) EXAM Questions & Answers, Well Elaborated | Already Verified Test |100% Verifi…




DTSA 5505 - Data Mining Methods (Study Cards)
EXAM Questions & Answers, Well Elaborated |
Already Verified Test |100% Verified solutions
|2026 Latest!!

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Terms in this set (103)



market basket analysis an unsupervised data mining technique for
determining sales patterns


Frequent Pattern Mining closed pattern X = no super-pattern Y given X with
the same support; max-pattern X = no super-
pattern Y given X


Apriori Algorithm A fast method of finding frequent itemsets, which
also involves pruning non-frequent items and self-
joining of k-itemsets only if their first (k-1) items are
the same.




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What challenges are there with multiple scans of whole dataset, huge number of
apriori algorithm? candidates, support counting of all candidates


Improvements for apriori algorithm? Partitioning, Sampling, Transaction reduction


Vertical data format Mining frequent itemsets using the
________________________ is a method that transposes the
rows of a given data set into columns.


FP-Growth Algorithm If 'd' is frequent in DB | abc, then abcd is frequent
(avoid candidate generation)


Association Rules Association rules specify a relation between
attributes that appears more frequently than
expected if the attributes were independent.


Correlation rules Measure of dependent/correlated events: lift(A,B) =
P(A U B) / P(A)P(B)


Rules of lift (correlation) lift = 1 (independent), lift > 1 (positive), lift < 1
(negative)


Metarule-Guided Mining P1 and P2 and ..... and Px => Q1 and Q2 and .... and
Qy


Supervised Learning Predefined classes, training data with groundtruth
label




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