Abstract
In the day to day job of a Network Manager at Bellsouth there are many decisions which have to be made. One such decision opportunity arose about one week ago. The question was what to do with a major cable which is in the way of a guard rail that the Department of Transportation is installing. In this paper, the decision on what to do with this cable will be solved using a decision tree. The discussion will include the major factors involved in making the decision and also show how the final decision was made.

Decision tree
The decision tree is an effective way to make a business decision; because you can write out multiple alternatives and different options that will go along with these alternatives. To show how effective the decision tree is, this paper will demonstrate how a Network Manager at Bellsouth will handle a situation that has come about due to the Department of Transportation (DOT) needing to add a guardrail to a road in which a major cable is in the way.

When using a decision tree one should start with the question, which in this case is what to do with the major cable. Then branch out from there with at least two options of what to do next. In this case there are three options: one would be to work with the DOT and move the cable as needed, two would be to replace the cable in another spot before the DOT started working, or three to hang this section of cable in the air. All three of these options are feasible, but only one is the best decision to make. The challenge is to come up with the best decision using the decision tree. And by diagramming the decision analytically the decision will be a more informed. (Hullett & Hillson, 2006).

These three options each need to be branched out twice more one branch for cost and the other branch for time. The first option: working with the DOT and moving the cable as needed is very cost efficient for my company because there would be no materials to buy and the only cost involved would be...

...DecisionTree Portfolio 1
DecisionTree Portfolio
Psy 410
Kathleen McCabe
University of Phoenix
January 21, 2012
Lara Ashbaugh
DecisionTree Portfolio 2
The Portfolio for my DecisionTree is concerning a residential fire. The first place that would be called is 911. The dispatchers in our area immediately contact the local and closest fire station(s) to respond. The following takes place after 911 has been called. The 911 dispatchers contact the police and fire departments arrive, the firefighters ensure the house has been vacated and all residents have been accounted for. If the family has pets they are accounted for as well, if possible. The first responders assist with contacting other agencies to find shelter for the family.
One of our local agencies is The Community Action Partnership which can secure shelter for the evening and longer, provide clothing, food, medications, and hygiene supplies. Health and welfare services are contacted which include emergency health care and emergency funds. If medical evaluations are necessary the support systems will ensure that the victims are taken to the hospital for care.
* What is the best way to access the organization’s services?
The first responders are contacted through 911.
The Community Action Partnership
1910 Industrial Way
Coeur d’Alene, ID 83815
208-664-8757...

...Group 2
Forest Cover Type
Prediction
ATUL JENA
RAJAT JAIN
SAHIL LALWANI
SAGNIK MAZUMDER
SHRADHA SANTUKA
Business Problem
To predict the forest cover type (the predominant kind of tree
cover) from strictly cartographic variables (as opposed to
remotely sensed data)
7 Cover types
Spruce/f
r
Lodgepol
e Pine
Ponderos
a Pine
Cottonwo
od/
Willow
Aspen
DouglasFir
Krummh
olz
Getting familiar with data
The source
Forest Cover data
set
Training set
15120
observation
s
Test set
565892
observation
s
Getting familiar with data
Description of attributes
40 soil types ( 0= absence or 1= presence )
Elevation, Aspect
Slope
4 areas of wilderness ( 0= absence or 1= presence )
Horizontal distance to Hydrology and Vertical distance to hydrology
HIllshade (9am/noon/3pm)
Horizontal distance to roadways
Horizontal distance to firepoints
Pre-Processing
Filter:
Excludes certain observations such as extreme outliers and errant data
Default filtering method: standard deviation from mean
Cut-off was set to 3 standard deviation (1637 observations filtered)
Data partition
Partition allocation:
Training 70% Validation 30% Test 0%
No. of observations:
Training 9433
Validation 4050
Pre-Processing (contd.)
Transformation
Used to stabilise variance, remove non-linearity, improve additivity and
counter non-normality
Default method: Maximum normal
Reduces skewness
Variable selection
Helps reduce the number of...

...
Decisiontree analysis
Decisiontree analysis known as an analytical tool applied to decision-making under condition of uncertainty, also clarifying where there are many possible outcomes for various alternatives and some outcomes are dependent on previous outcomes. However, decisiontree will present as a diagram by showing the relationship among possible courses of action, possible events and the potential outcomes for each course of action in the decision (Drury, 2012). So decisiontree analysis is useful for merchant navy company to understand in what direction their chance events are and what their values in terms of profits and losses are for each of the two tooling alternatives, also visualize the outcomes of different prospects in order make better decision under uncertainty
Strengths of decisiontree analysis
Decisiontree analysis will show all the alternatives, probabilities, costs and the possible outcomes that are not even consider by the company. The company can add the possible scenario into decisiontree diagram, through the diagram can calculate the expected values and a probability distribution in more complex situations and the attributes can be chosen in any desired order (Kirkwood, 2002).
Weaknesses of...

...Lab 1: Decision Trees and Decision Rules
Evgueni N. Smirnov
smirnov@cs.unimaas.nl
August 21, 2010
1. Introduction
Given a data-mining problem, you need to have data that represent the problem, models that are suitable for the data, and of course a data-mining environment that contains the algorithms capable of learning these models. In this lab you will study two well-known classification problems. You will try to find classification models for these problems using decision trees and decision rules. The algorithms to learn these models are given in Weka, a data-mining environment that accompanies our course. You will study the explorer part of Weka to learn how to call decision-tree and decision-rule algorithms, how to evaluate the accuracy of the learned models, and how to use reduced error pruning.
2. Concept-Learning Problems
In this lab you are expected to build classification models for two classification problems:
• Labor-negotiation problem;
• Soybean classification problem.
The data files for all the two problems are provided in the directory:
http://www.unimaas.nl/datamining/UCI/datasets-UCI.zip
3. Environment
As stated above to build the desired classification models you will use Weka. Weka is a data-mining environment that contains a collection of machine-learning algorithms for...

...Decision Analysis
Course Outline, Quarter I, 2006
Class Materials Topic
Hardcopy in Packet Other*
Introduction
1 Freemark Abbey Winery Structuring Decisions
Framework for Analyzing Risk
2 The North Star Concert North Star.xls Best Guess, Worst Case, Best Case; and Continuous Uncertainties
3 Engine Services, Inc.
Quick Start Guide to Crystal Ball
Analyzing Uncertainty, Probability Distributions, and Simulation Learning Module: Crystal Ball Litigate Demo
Engine Services.xls Language of Probability Distributions and Monte Carlo Simulation
4 Taurus Telecommunications Corporation: A New Prepaid Phone Card Learning Module: Tornado Sensitivity
Taurus Telecommunications.xls Sensitivity Analysis and Key Drivers
Time Value of Money
5 Dhahran Roads (A)
Evaluating Multiperiod Performance Multiperiod Pro Forma and NPV
6 Roadway Construction Company NPV, IRR, and Project Assumptions
Data and Distributions
7 Appshop, Inc. Simulating NPV
8 Lorex Pharmaceuticals
Introduction to Analytical Probability Distributions Lorex Exhibit 2.xls Distributions
9 Sprigg Lane (A) Sprigg2.xls Probability Distributions and Spreadsheet Modeling; Risk
10 The Waldorf Property
Chapter 11 of QBA: Text and Cases
Waldorf.xls Cumulative Distribution Functions, Adjustment for Risk
11 Amore Frozen Foods (A) Macaroni and Cheese Fill Targets
Sampling Amore.xls Sample Uncertainty
Regression
12 Hightower Department Stores: Imported Stuffed Animals...

...Decision Trees The DecisionTree 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 DecisionTree Module the screen will appear as in Figure 1 below.
Figure 1: The InitialDecisionTree Screen
Notice the DecisionTree Creation Window on the right. This is used to perform all of the work of constructing the tree. The initial screen has 1 starting node (Node 1) which can be seen in cell A6. The first step is to add branches from this node. The default setting is to Add 2 Decision branches. The type of branch is selected by the choice of “Add” buttons that is selected and the number of branches is selected by the textbox/scrollbar combination. For this example, there are three options – Purchase CAD, Hire Engineers or Do Nothing. Therefore we will change the number of branches to 3 and click on the “Add Decisions” button. This yields the screen as displayed in Figure 2.
Decision Trees.doc
Page 1 of 7
Figure 2: The First Three Branches
At this point the data can be entered into the shaded green cells. For decision...

...On: DecisionTree Approach Submitted to: Md.Torikul Alam Professor Department of Business Administration Asian university of Bangladesh (Motijheel Campus) Submitted by: MD.SHOAIB ID:201121285 FEROZE MAHMUD MOJUMDER ID: 201120558 Semester: Fall Batch : 42nd Submission date: December 07, 2012
Introduction to Decision Analysis • • • The field of decision analysis provides a framework for making important decisions.Decision analysis allows us to select a decision from a set of possible decision alternatives when uncertainties regarding the future exist of a decision criterion... The goal is to optimize the resulting payoff in terms.
Definition of 'DecisionTree' A schematic tree-shaped diagram used to determine a course of action or show a statistical probability. Each branch of the decisiontree represents a possible decision or occurrence. The tree structure shows how one choice leads to the next, and the use of branches indicates that each option is mutually exclusive. In decision analysis, a decisiontree can be used to visually and explicitly represent decisions and decision making. In data mining, a decisiontree describes data but not...

...DecisionTree Analysis
Choosing Between Options
by Projecting Likely Outcomes
Decision Trees are useful tools for helping you to choose between several courses of action.
They provide a highly effective structure within which you can explore options, and investigate the possible outcomes of choosing those options. They also help you to form a balanced picture of the risks and rewards associated with each possible course of action. This makes them particularly useful for choosing between different strategies, projects or investment opportunities, particularly when your resources are limited.
How to Use the Tool
You start a DecisionTree with a decision that you need to make. Draw a small square to represent this on the left hand side of a large piece of paper, half way down the page. From this box draw out lines towards the right for each possible solution, and write a short description of the solution along the line. Keep the lines apart as far as possible so that you can expand your thoughts.
At the end of each line, consider the results. If the result of taking that decision is uncertain, draw a small circle. If the result is another decision that you need to make, draw another square. Squares represent decisions, and circles represent uncertain outcomes. Write the decision or factor above the square or circle. If you have...