Data Anaysis 2

Question 1

Define classification (context: data mining)

Answer 1

Classification - classifying attributes into target categories, e.g. customers into low medium or high average earnings

Question 2

Define clustering (context: data mining)

Answer 2

Clustering - Grouping data into clusters so they can be treated as groups - e.g. customers based on geographic regions

Question 3

Define anomaly/outlier detection (context: data mining)

Answer 3

Anomaly/Outlier detection - finding unexpected patterns in data

Question 4

Define association rule mining (context: data mining)

Answer 4

Association rule mining - establishing a relationship between 2 data events

Question 5

Define sequential patterns (context: data mining)

Answer 5

Sequential patterns - tracing a series of events that take place in a sequence

Question 6

Define affinity grouping (context: data mining)

Answer 6

Affinity grouping - discovering co-occurrence in relationships

Question 7

Define decision trees (context: data mining)

Answer 7

Decision trees - tree structure where each branch represents a probable occurrence

Question 8

Define regression (context: data mining)

Answer 8

Regression - Identifying the nature of a relationship between 2 variables, e.g. causal