PPT-Decision Trees & Rule-based AI

Decision Tree Advantages Fast and easy to implement Simple to understand Modular Reusable Can be learned can be constructed dynamically from observations and actions in game we will discuss this further in a future topic called Learning. Battiti. , Mauro . Brunato. .. The LION Way: Machine Learning . plus.  Intelligent Optimization. .. LIONlab. , University of Trento, Italy, . Apr 2015. http://intelligent-optimization.org/LIONbook. Arko. . Barman. Slightly edited by Ch. . Eick. COSC 6335 Data Mining. Decision Trees. Used for classifying data by partitioning attribute space. Tries to find axis-parallel decision boundaries for specified optimality criteria. A . decision tree. is a graphical representation of every possible sequence of decision and random outcomes (states of nature) that can occur within a given decision making problem.. A decision tree is composed of a collection of nodes (represented by circles and squares) interconnected by branches (represented by lines).. Correct Answer – False (Decision 14-3/9). Correct Answer – False (Rule 5-2). Correct Answer – True (Decision 4-3/1). Correct Answer – True (Decision 14-3/18). Correct Answer – True (Decision 4-4c/1). Pre-test. Which mammal is the pig more closely related to, cow or camel?. Which mammal here is the most primitive?. Fig. 4.8b. Common ancestor. Root of the tree. Nodes. Terminal taxa (tips). Branches. A . tree. is a connected undirected graph with no simple circuits.. Since a tree cannot have a simple circuit, a tree cannot contain multiple edges or loops.. Therefore, any tree must be a . simple graph. Dr. Halimah Alshehri. 1. Introduction to Trees. DEFINITION 1 . A . tree. is a connected undirected graph with no simple circuits.. Because . a tree cannot have a simple circuit. , . a tree cannot contain multiple edges or loops. Copyright © Andrew W. Moore. Density Estimation – looking ahead. Compare it against the two other major kinds of models:. Regressor. Prediction of. real-valued output. Input. Attributes. Density. Estimator. Chapter 5 Divide and Conquer – Classification Using Decision Trees and Rules decision trees and rule learners two machine learning methods that make complex decisions from sets of simple choices AVL Trees 1 AVL Trees 6 3 8 4 v z AVL Trees 2 AVL Tree Definition Adelson- Velsky and Landis binary search tree balanced each internal node v the heights of the children of v can differ by at most 1 Decision trees MARIO REGIN What is a decision tree? General purpose prediction and classification mechanism Emerged at the same time as the nascent fields of artificial intelligence and statistical computation 6. 9. 2. 4. 1. 8. <. >. =. © 2014 Goodrich, Tamassia, Goldwasser. Presentation for use with the textbook . Data Structures and Algorithms in Java, 6. th. edition. , by M. T. Goodrich, R. Tamassia, and M. H. Goldwasser, Wiley, 2014. . by Holly Nguyen, Hongyu Pan, Lei Shi, Muhammad Tahir. Showcasing work by . Themis P. Exarchos, Alexandros T. Tzallas, DinaBaga, Dimitra Chaloglou, Dimitrios I. Fotiadis, Sofia Tsouli, Maria Diako. u. Pablo Aldama, Kristina . Vatcheva. , PhD. School of Mathematical & Statistical Sciences, University of Texas Rio Grande Val. ley. Data mining methods, such as decision trees, have become essential in healthcare for detecting fraud and abuse, physicians finding effective treatments for their patients, and patients receiving more affordable healthcare services (.