Freemark Abbey Winery Group ZZZ 1. Construct the decision tree for William Jaeger. 2. What should he do? Jaeger should choose to harvest later and wait for the storm. If the storm does come but destroys the grapes, he can decide whether to bottle wine or not to protect winery’s reputation. In either way, he will gain higher revenues from harvesting later than harvesting immediately: EV of “Do not harvest & Bottling”: $39240 EV of “Do not harvest & Not bottling”: $39240-$12000*0
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Effect of Broken Home on Student Academic Performances investigating the effect of students socio-economic/family background on students academic performance in tertiary institutions using decision tree algorithms A. B. Adeyemo (Ph.D)1 and S. O. Kuyoro (M.Sc.)2 Department of Computer Science, University of Ibadan, Ibadan, Nigeria Abstract The causes of the difference in the academic performance of students in tertiary institutions has for a long time been the focus of study among higher education
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Mr. Warren operated a real estate agency that specialized in finding buyers for commercial properties. Warren was approached one day by a prospective client, who had three properties that he wished to have sold. The client wished to receive the following prices: Property Price Allston $25,000 Belmont $50,000 Cambridge $100,000 Warren would receive a commission of 4% on any of the properties he was able to sell. The client laid down the following conditions for an exclusive listing: (i)
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Let’s suppose the prediction for the sales demand that Ann Queen derived from other comparable events is accurate. It is relatively easy to figure out the possible DVDs that can be sold with expected probability if we draw a decision tree. From the above tree graph, we can tell that the total possibility to sell 4000 DVDs in Saturday and Sunday is 25%. If Ann Queen’s expectation about the possibility of DVD sold is accurate and nothing new information will be available after Friday’s and Saturday’s
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financial theory to analyze real life situations in an uncertain environment with an incomplete data set. It is integrative in nature, with special attention to the integration of theory and managerial judgment in the process of making financial decisions. BSBA Goals BSBA students will graduate being Effective Communicators, Critical Thinkers, Able to Analyze Ethical Problems, Global in their perspective, and Knowledgeable about the essentials of business. This class contributes to those goals through
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MIS 344 HOMEWORK#1 (DUE DATE 23.03.2012) 1. The Technically Techno Company has several patents for a variety of different Flash memory devices that are used in computers, cell phones, and a variety of other things. A competitor has recently introduced a product based on technology very similar to something patented by Technically Techno last year. Consequently, Technically Techno has sued the other company for copyright infringement. Based on the facts in the case as well as the record of the
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A NOTE ON CONSTRUCTING INFLUENCE DIAGRAMS Influence diagrams were devised as a way to graphically depicting the relationship between several elements that can affect the results of a decision. The diagram can be used as a basis for creating computer-based models that describe a system or as descriptions of mental models managers use to assess the impact of their actions, see Senge (4 ). For more information on influence diagrams see Bodily et al (1) ; Bossel(2); or Plane(3). This note explains
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Decision Trees The Decision Tree module in Excel OM (and in POM for Windows) acts differently than all other modules because rather than creating a table of data it creates a graphical tree. We will use Example 3 in Chapter A5 from Heizer & Render’s Operations Management textbook for our example. After selecting the Decision Tree Module the screen will appear as in Figure 1 below. Figure 1: The Initial Decision Tree Screen Notice the Decision Tree Creation Window on the right. This is used
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See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/296695247 USING DATA MINING TO PREDICT SECONDARY SCHOOL STUDENT ALCOHOL CONSUMPTION Dataset · February 2016 DOI: 10.13140/RG.2.1.1465.8328 READS 2,200 2 authors: Fabio Pagnotta Hossain Amran University of Camerino University of Camerino 8 PUBLICATIONS 0 CITATIONS 5 PUBLICATIONS 0 CITATIONS SEE PROFILE All in-text references underlined in blue
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attribute for “TYPE” which could be either ITALIAN or FRENCH. Define an algorithm for dealing with missing attributes and partially specified attributes,which includes the modified calculation for information gain use to make splitting decisions. Generate a decision tree for this example using your new algorithm. Answer There are a lot of ways of answering this question. One algorithm is as follows: For a training instance with multivalued attributes, I will duplicate that instance by the number
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