ISYE 6501 Glossary WITH CORRECT
QUESTIONS AND 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.)
QUESTIONS AND 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.)
