Analytics #2 Exam

To identify patterns across transactions, we can use

association rules

The process of extracting useful information from text data is known as __________.

text mining

Which of the following is true of Euclidean distances?

It is commonly used as a method of measuring dissimilarity between quantitative observations.

Which statement is true of an association rule?

It is ultimately judged on how actionable it is and how well it explains the relationship between item sets.

__________ approaches are designed to describe patterns and relationships in large data sets with many observations of many variables.

Unsupervised learning

The data preparation technique used in market segmentation to divide consumers into different homogeneous groups is called

cluster analysis

An analysis of items frequently co-occurring in transactions is known as

market basket analysis

In k-means clustering, k represents the

number of clusters

Euclidean distance can be used to measure the distance between __________ in cluster analysis.

observations

Observation refers to the

set of recorded values of variables associated with a single entity

The process of converting a word to its stem, or root word, is referred to as __________.

stemming

A __________ refers to the number of times a collection of items occurs together in a transaction data set.

support count

In the text mining process, the text is first preprocessed by deriving a smaller set of _________ from the larger set of words contained in a collection of documents.

tokens

k-means clustering is the process of

organizing observations into distinct groups based on a measure of similarity.