MA Chapter 4
Identify the antecedent of the following association rule: "if {cereal}, then {milk}."
Cereal
The goal of _____________ is to segment observations into similar groups based on the observed variables.
Clustering
The ____________________ clustering method defines the similarity between two clusters as the similarity of the pair of observations (one from each cluster) that are the most different.
Complete Linkage
T/F Complete linkage is a measure of calculating dissimilarity between clusters by considering only the two CLOSEST observations in the two clusters.
False
The number of times that a collection of items occur together in a transaction data set is known as the sampling.
False
Analysis of items frequently co-occuring in transactions (such as purchases) is known as lift.
False, it is market basket analysis
__________________ is bottom-up clustering that starts with each observation belonging to its own cluster and then sequentially merges the most similar clusters to create a series of nested clusters.
Hierarchical clustering
The __________________ the lift ratio, the _________________ the association rule.
Higher, stronger
__________________ assigns each observation to one of k clusters in a manner such that the observations assigned to the same cluster are as similar as possible.
K-Means Clustering
Which of the following explicit measures does not help to filter association rules?
Lift Ratios
________________________ analyzes items frequently co-occuring in transactions (such as purchases).
Market basket analysis
Single linkage is a measure of calculating the distance between two clusters by considering only the two _______________ observations between the two clusters.
Most similar
If the Euclidean distance were to be represented in a right triangle, which of the following would be considered the distance between two objects of a cluster?
The hypotenuse
Support Count
The number of times that a collection of items occur together in a transaction data set.
Interpret the following association rule: "if {ground beef, cheese}, then {taco shells}."
This means that if a transaction includes taco shells then it also includes ground beef and cheese.
Complete linkage is a measure of calculating dissimilarity between clusters by considering only the two MOST DISSIMLAR observations in the two clusters.
True
Euclidean distance can be used to measure the distance between two observations each consisting of two variable measurements.
True
If the support of the consequent is high, the confidence of the association rule could be high even if there is little or no association between the items.
True
T/F Association rules convey the likelihood of certain items being purchased together.
True
T/F Centroid linkage uses the averaging concept of cluster centroids to define between-cluster similarity.
True
T/F Euclidean distance is the most common method to measure dissimilarity between observations.
True
T/F The item set corresponding to the "if" portion of an if-then association rule is called the antecedent.
True
The efficiency of an association rule, known as lift, is determined by the ratio of the confidence of an association rule to the benchmark confidence.
True
Identify the consequent of the following association rule: "if {jello, pudding}, then {whipped cream}."
Whipped cream
Confidence can be viewed as a conditional probability of the consequent item set occurring given that the
antecedent items sets occurs
Complete linkage defines the similarity between two clusters as the similarity of the pair of observations (one from each cluster) that
are the most different
Ward's method merges two clusters such that the dissimilarity of the observations within the resulting single cluster increases _______________.
as little as possible
There are infinitely many possible association rules for transaction data. To simplify, we only consider association rules with a support count of
at least 20% of the total number of transactions
The item set corresponding to the "then" portion of an if-then association rule is called the
consequent
The lift ratio demonstrates some usefulness to the association rule if its value is
greater than 1
Euclidean distance can be used to measure the distance between ________________ in cluster analysis.
observations
Marketers are interested in examining transaction data on customer purchases to identify
the products that are commonly purchased together.
Lift Ratio
the ratio of confidence to benchmark confidence, another measure of the strength of an association rule.