ISYE 6501 Glossary Questions with
Correct Answers
, Algorithm - CORRECT ANS:Step-by-step procedure designed to carry out a task
Change detection - CORRECT ANS:Identifying when a significant change has taken place in a process.
Classification - CORRECT ANS:The separation of data into two or more categories, or (a point's
classification) the category a data point is put into.
Classifier - CORRECT ANS:A boundary that separates the data into two or more categories. Also (more
generally) an algorithm that performs classification.
Cluster - CORRECT ANS:A group of points identified as near/similar to each other.
Cluster center - CORRECT ANS:In some clustering algorithms (like 𝑘-means clustering), the central point
(often the centroid) of a cluster of data points.
Clustering - CORRECT ANS:Separation of data points into groups ("clusters") based on
nearness/similarity to each other. A common form of unsupervised learning.
CUSUM - CORRECT ANS:Change detection method that compares observed distribution mean with a
threshold level of change. Short for "cumulative sum".
Deep learning - CORRECT ANS:Neural network-type model with many hidden layers.
Dimension - CORRECT ANS:A feature of the data points (for example, height or credit score). (Note that
there is also a mathematical definition for this word.)
EM algorithm - CORRECT ANS:Expectation-maximization algorithm.
Correct Answers
, Algorithm - CORRECT ANS:Step-by-step procedure designed to carry out a task
Change detection - CORRECT ANS:Identifying when a significant change has taken place in a process.
Classification - CORRECT ANS:The separation of data into two or more categories, or (a point's
classification) the category a data point is put into.
Classifier - CORRECT ANS:A boundary that separates the data into two or more categories. Also (more
generally) an algorithm that performs classification.
Cluster - CORRECT ANS:A group of points identified as near/similar to each other.
Cluster center - CORRECT ANS:In some clustering algorithms (like 𝑘-means clustering), the central point
(often the centroid) of a cluster of data points.
Clustering - CORRECT ANS:Separation of data points into groups ("clusters") based on
nearness/similarity to each other. A common form of unsupervised learning.
CUSUM - CORRECT ANS:Change detection method that compares observed distribution mean with a
threshold level of change. Short for "cumulative sum".
Deep learning - CORRECT ANS:Neural network-type model with many hidden layers.
Dimension - CORRECT ANS:A feature of the data points (for example, height or credit score). (Note that
there is also a mathematical definition for this word.)
EM algorithm - CORRECT ANS:Expectation-maximization algorithm.
