PPT-Decision Trees: Another Example

Training Set Play Tennis Weak Rain Mild High Weak No Rain Mild High Weak No Decision Trees Another Example Training Set Play Tennis Sunny Weak. Figure 1 Analysis Figure 2 brPage 3br dI dT Object Moment of Inertia I kgm Period For One Oscillation s Table 1 Figure 3 I I brPage 4br I T T I Conclusion References T state 8712X action or input 8712U uncertainty or disturbance 8712W dynamics functions XUW8594X w w are independent RVs variation state dependent input space 8712U 8838U is set of allowed actions in state at time brPage 5br Policy action is function 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).. Classify as positive if K out of 30 trees Classify as positive if K out of 30 trees predict positive. Vary K.predict positive. Vary K. Generating ROC CurvesGenerating ROC Curves Linear Threshold Uni Decision Trees. Gavin Brown. www.cs.man.ac.uk/~gbrown. Recap: threshold classifiers. height. weight. Q. Where is a good threshold?. 10 20 30 40 50 60. 1. 0. Also known as “decision stump”. From Decision . Training Set:. Play Tennis?. Weak. Rain Mild High Weak No. Rain Mild High Weak No. Overfitting. /. Underfitting. in Decision Trees. Over-fitting vs. Under-fitting. Sibel Adali, . Sujoy Sikdar. , Lirong Xia. Multi-Issue Voting. { , } . X. . { , }. Wine (. ).  . Main dishes (. ).  . Goal: Cater to people’s preferences. issues. Object-based classifiers. Others. DECISION TREES. Non-parametric approach. Data mining tool used in many applications, not just RS. Classifies data by building rules based on image values. Rules form trees that are multi-branched with nodes and “leaves” or endpoints. 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. Statin Choice Decision Aid Share-Decision Making SCIP Shared Decision Making Shared Decision Making Glasziou and Haynes ACP JC 2005 Promote a process where patients and clinicians make a choice together. 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 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 (.