Decision Tree Model - 3401 Words

Instructor’s Manual Chapter 1 1 Chapter 1 I 1.1 Chapter Outline A Decision Tree Model and Its Analysis †¢ The following concepts are introduced through the use of a simple decision tree example (the Bill Sampras summer job decision): Decision tree Decision node Event node Mutually exclusive and collectively exhaustive set of events Branches and final values Expected Monetary Value (EMV) Optimal decision strategy †¢ Introduction of the folding back or backward induction procedure for solving a decision tree. †¢ Discussion on sensitivity analysis in a decision tree. Summary of the General Method of Decision Analysis. Another Decision Tree Model and Its Analysis †¢ Detailed formulation, discussion, and solution of the†¦show more content†¦If the forecast indicates a rainy day, she should cancel the show. If the forecast indicates a sunny day, she should continue with the show. The EMV of this strategy is $6,200. Manual to accompany Data, Models Decisions: The Fundamentals of Management Science by Bertsimas and Freund. Copyright 2000, South-Western College Publishing. Prepared by Manuel Nunez, Chapman University. Instructor’s Manual Chapter 1 4 1.2 (a) See decision tree above. (b) Once Monday s bid is made, Newtone s optimal strategy is to accept the bid if it is a $3,000,000 bid and reject it if the bid is for $2,000,000. If Monday s bid is rejected, then accept Tuesday s bid, regardless of the amount offered. The EMV of this strategy is $2,600,000. Manual to accompany Data, Models Decisions: The Fundamentals of Management Science by Bertsimas and Freund. Copyright 2000, South-Western College Publishing. Prepared by Manuel Nunez, Chapman University. Instructor’s Manual Chapter 1 5 1.3 (a) As shown in the table below, as p decreases James optimal decision changes as to take Meditech s offer. A break-even analysis where we solve the equation 440p - 200(1-p) = 150 reveals that the break-even probability is p=0.55. In other words, if the probability of successful 3D software is below 0.55, then it is better for James to accept Meditech s offer, otherwise continue with the project. Probability of Successful 3D Development pShow MoreRelatedFuture Technology For E Health Systems1372 Words   |  6 Pagessystems. Here, I discuss various models built using SAS ® Enterprise Minerâ„ ¢ 14.1, on a free public domain dataset containing165,633 observations and 19 attributes and compare each model with another. Data used in this discussion, represents the metrics of accelerometers mounted on waist, left thigh, right arm and right ankle of 4 individuals performing five different activities recorded over a period of eight hours. Finally, I propose a Stepwise Logistic-fed-AutoNeural model to recognize human activityRead MoreProposed Stand Alone Store Near The Auburn Market1137 Words   |  5 Pagesdetails of this decision, it is important to understand the outcome and recommendation early in case there are key questions to answer during the presentation. A decision tree was used to analyze all of the data provided by Gloria Rodriguez. The results show that Shuzworld s hould build a stand-alone store in Auburn. The decision tree analysis has broken down the expected monetary value (EMV) for each alternative. In the decision tree, the squares represent decision nodes. A decision node is whereRead MoreHarimann International2893 Words   |  12 PagesDECISION SUPPORT MODEL Instructor: DR.DO BA KHANG CASE REPORT Harimann International REPORT CONTENT: CASE ABSTRACT 2 1/ Prepare a decision tree for the initial problem 2 2/ Do you agree with Mr. Dhawan’s analysis in Exhibit 3? 4 3/ Prepare a decision tree to include the different possible delivery dates of the embroider. Interpret the results. 5 4/ Prepare a decision tree to describe the situation with parallel production process 7 5/ Assuming thatRead MoreThe Regression Model Of The United States1762 Words   |  8 Pagesthe models that are based on the same data, so I tried to use the same variables and the same missing value treatment approach (excluding decision tree) to all of the models. All the 3 models showed a performance of nearly the same quality, according to the various lift charts produced and presented in the further parts of the report. However, the difference becomes more evident on the % captured response and the most efficient and useful model turns out to be the logistic regression model. ItRead MoreDeveloping A Credit Scoring Model2203 Words   |  9 Pagesâ€Å"good† credit risk and 300 are classified as â€Å"bad† credit risk. This report lists the detailed steps involved in developing a credit scoring model that can be used to determine if a new applicant is a good credit risk or a bad one, based on their predictor variables. Tools Used: SAS Enterprise Miner 4.3 IBM SPSS Statistics 22 Modeling Techniques Used: Decision Tree DATA PREPARATION AND EXPLORATION The modeling process incorporated in this project is based on the Enterprise Miner SEMMA methodology whichRead MoreDecision Analysis : Decision Tree Format Essay1778 Words   |  8 Pagesthe option to move to Houston or lease new space at Dallas after five years if the church survives. The concept of decision tree will be used in this paper to analyze each alternative to advice the management the best alternative with the lowest cost. Decision tree will be used in this analysis because it is a convenient way to lay out steps of a capacity problem. The decision tree format helps not only on understanding the problem but also in finding a solution. Read MoreThe Cost Effectiveness Of A Drug Or Treatment1291 Words   |  6 PagesExample decision tree analysis from the British Journal of Clinical Pharmacology [Ademi] One current method of studying cost effectiveness is called a decision tree analysis. It is used to illustrate a decision-making process for quantifying and comparing health strategies in terms of health effects and costs. Use of a decision tree allows users to explicitly view assumptions and inputs. An example of a hypothetical decision tree is showing in Figure 1 [Ademi]. Branches in the decision tree representRead MoreSteps of CART: Classification and Regression Tree746 Words   |  3 PagesOverview The classic CART: Classification and Regression Tree algorithm was created by Breiman. The CART method is binary recursive partitioning procedure that can be used to process both continuous and nominal attributes as targets and predictors. The binary splits are the splitting of the data represented by nodes; each node is split into two child nodes to represent the binary split on the data into two separate paths. The recursive part of CART means that any child nodes can be additionally splitRead MoreData Mining, Classification, And Association Rules1654 Words   |  7 PagesAbstract: Classification is one of the most familiar data mining technique and model finding process that is used for transmission the data into different classes according to particular condition. Further the classification is used to forecast group relationship for precise data instance. It is generally construct models that are used to predict potential statistics trends. The major objective of machine data is to perfectly predict the class for each record. This article focuses on a survey onRead MoreDiffculty Level Question Questions1681 Words   |  7 PagesQuestion Reference Solution Methodology Checked and verified for accuracy (Y/N) 1 2 Decision trees are considered under which class of Machine Learning Algorithms? Supervised Learning Unsupervised Learning Reinforcement learning Option 1 and 2 both Supervised Learning Supervised Learning Tree based Modelling 2 3 Decision tree  is a type of supervised learning algorithm (having a pre-defined target variable). Decision Trees can be used for _________ . Classification problems Regression problems Option