ML Outputs

Table of Contents

ML Outputs

Decision Table (p. 58)

Decision Table Problems

Decision Tree (p. 58)

Decision Tree Problems

Rules

Categorization of Rules (p.59)

Classification Rules (E.g.)

Class Rules ? Decision Trees

Rule Problems

Association Rules

Rules with Exceptions

Rules with Relations (rules w/ relational predicates)

‘Problems’ with Relational Rules

Numeric Value Predictors (p. 70)

Linear Regression 

Tree Numeric Predictors (p. 70)

Instance-based Representation (p.72)

Features of Instance Methods 

Clusters (p75)

Email: riggs@cis.famu.edu

Home Page: http://www.cis.famu.edu/~riggs/riggs.html

Other information:
Datamining Dr. Riggs Summer B 2000