Decision Tree

Aug 30, 2012

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Decision tree. Examples. Decision Tree. . Decision tree algorithm . concept. . New example. . classification. Decision tree for the concept Enjoysports. Outlook. Humidity. Wind. . . . . . . Sunny. Rain. High. Normal. Strong. Weak. No. Yes. No. Yes. Decision tree for Enjoysports. Humidity. Airtemp. A

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Decision Tree

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1. Decision Tree

Decision tree

Decision tree LING 572 Fei Xia 1/16/06 Outline Basic concepts Issues  In this lecture, “attribute” and “feature” are interchangeable. Basic concepts Main idea Build a tree  decision tree Each node represents a test Training instances are split at each node Greedy algorithm

1.22k views • 45 slides

Decision tree

Decision tree. LING 572 Fei Xia 1/10/06. Outline. Basic concepts Main issues Advanced topics. Basic concepts. A classification problem. Classification and estimation problems. Given a finite set of (input) attributes: features Ex: District, House type, Income, Previous customer

779 views • 42 slides

Decision Tree

Decision Tree. Decision Tree.

262 views • 3 slides

Decision tree

Decision tree. LING 572 Fei Xia 1/16/06. Outline. Basic concepts Issues  In this lecture, “attribute” and “feature” are interchangeable. Basic concepts. Main idea. Build a tree  decision tree Each node represents a test Training instances are split at each node Greedy algorithm.

992 views • 45 slides

Decision Tree

Decision Tree. Saed Sayad. Decision Tree (Mitchell 97).

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DECISION TREE

DECISION TREE. Developed for the National Petroleum Technology Office By Brian Keltch & Andrew Hastings bkeltch@npto.doe.gov (918) 699-2065 TRW. Presented By Len Volk. What Is It?. Computer program Aids making decisions & risks in these decisions Organizes available information

388 views • 27 slides

Decision Tree Modeling

Decision Tree Modeling. Decision Trees Software demonstration Introduction to ICI case. Decision Analysis.

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Decision Tree Classifiers

Decision Tree Classifiers. Abhishek Agarwal CS 5368: Intelligent Systems Fall 2010. Paradigms of learning Reinforcement Learning The agent receives some evaluation of actions (like fine for stealing bananas) but is not told the correct action (such as how to buy bananas)

429 views • 26 slides

DECISION TREE

DECISION TREE. Project Risk Management: A combined Analytic Hierarchy Process and Decision Tree Approach Dr.Prasanta Kumar Dey. CONTENT. What is the decision tree? The example of decision tree The advantage of decision tree The application of decision tree. WHAT IS THE DECISION TREE?.

1.78k views • 37 slides

Decision Tree

Decision Tree. LING 572 Fei Xia, Bill McNeill Week 2: 1/15/09. Main idea. Build a tree  decision tree Each node represents a test Training instances are split at each node Greedy algorithm. A classification problem. Decision tree. District. Suburban (5). Urban (5). Rural (4).

676 views • 43 slides

Decision Tree Learning

Lehrstuhl für Informatik 2. Gabriella Kókai: Maschine Learning. Decision Tree Learning. Contents. Introduction Decision Tree representation Appropriate problems for Decision Tree learning The basic Decision Tree learning algorithm (ID3) Hypothesis space search in Decision Tree learning

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Decision Tree

The decision tree is the classification algorithm in ML(machine learning). A decision tree is a decision support tool that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. To understand the algorithm of the decision tree we need to know about the classification. https://www.learnbay.co/data-science-course/blog-post/decision-tree/

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Decision Tree

Decision Tree. Colleen K. McIlvennan, DNP, ANP Assistant Professor of Medicine Section of Advanced Heart Failure and Transplantation INTERMACS 2016. Disclosures. None. Outline. What is Shared Decision Making? LVAD Therapy (DT) Decision Support Tools. 1. What is Shared Decision Making?.

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Decision Tree

Decision Tree. Developed by: Dr Eddie Ip Modified by: Dr Arif Ansari. Outline. Example Concept. Decision Tree: Example 1. Life insurance: whether preferred rate should be given? ID low risk group & give preferred rate Criteria: smoking ? overweight ?. Decision Tree: Example 2.

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Decision Tree

Decision Tree. Rong Jin. Determine Milage Per Gallon. A Decision Tree for Determining MPG. mpg cylinders displacement horsepower weight acceleration modelyear maker 4 low low low high 75to78 asia. good. From slides of Andrew Moore. Decision Tree Learning. Extremely popular method

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Decision Tree

Decision Tree. Decision Tree. Outlook. Sunny. Overcast. Rain. Humidity. Yes. Wind. High. Normal. Strong. Weak. No. Yes. No. Yes. Outlook. sunny. overcast. rain. overcast. humidity. windy. P. high. normal. false. true. N. P. N. P. An Example. categorical.

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Decision Tree

Decision Tree. Classification. Databases are rich with hidden information that can be used for making intelligent decisions. Classification is a form of data analysis that can be used to extract models describing important data classes. Data classification process. Learning

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