Dec 16, 2015 - Kaplan Decision Tree NCLEX: Nursing Decision Tree, Nursing Med, Nclex ...:. The Decision Tree procedure creates a tree-based classification model. List the Clinical Pharmacology characteristics of an Ideal ... Decision Tree Investigational Agent Chronic, Systemic Drug, Use Likely in Hepatically impaired Single-Use, Inhalational Decision trees are decision support models that classify patterns using a sequence of well-defined rules. A decision tree is an algorithm for supervised learning. A decision tree can help us to solve both regression and classification problems. It became a concern to everyone in both society and the family. Conclusions: Our findings suggest that a clinical decision tree can be used to estimate a bacteremic … But with Canva, you can create one in just minutes. Saved from images.search.yahoo.com. Simply choose a decision tree template and start designing. Natural occurrence in body or in traditional foods Cramer GM, Ford RA, Hall RL (1978). Click the orange nodes to make a decision and expand the next level of the tree. Thus our aim is to develop a decision tree … Use the Basic Flowchart template, and drag and connect shapes to help document your sequence of steps, decisions and outcomes. We find that suitably defined decision trees can help to resolve gene regulatory programs involved in shaping lineage trees. An Anticyanide Decision Tree Network (DTN) has been designed to rapidly identify drugs which, when used on a short-term basis before expected agent exposure or immediately after exposure, will be … Based on the answers, each question leads to an outcome. A decision tree model is non-parametric in nature i.e., it uses infinite parameters to learn the data. 3. Decision trees that are trained on any training data run the risk of overfitting the training data.. What we mean by this is that eventually each leaf will reperesent a very specific set of attribute combinations that are seen in the training data, and the tree will consequently not be able to classify attribute value combinations that are not seen in the … He started losing interest. Yahoo Image Search. Decision Tree Examples. It is a tree-structured classi f … Assign the probability of occurrence for all the risks. This preview shows page 1 - 3 out of 5 pages. Decision trees should begin with a central theme or question you are trying to answer. FEMALE BIPOLAR DEPRESSION DECISION TREE 3 Decision 1 According to treatment guidelines published in a report by the American Psychiatric Association (Hirschfeld et al., 2010) lithium is the first line of treatment for the acute manic stages of bipolar depression. As you will see, machine learning in R can be incredibly simple, often only requiring a few lines of code to get a model running. All it takes is a few drops, clicks and drags to create a professional looking decision tree … Use the tree to talk through every possible choice, figure out alternatives, and build out additional branches as needed. Estimation of Toxic Hazard - A Decision Tree … • Decision tree containing 33 (Y/N) questions applied in sequence • Three important considerations: 1. Decision Tree algorithm has become one of the most used machine learning algorithm both in competitions like Kaggle as well as in business environment. For complete information on flowcharts and the shapes commonly used, see Create a basic flowchart. Decision tree for regression 1 if x2<3085.5 then node 2 elseif x2>=3085.5 then node 3 else 23.7181 2 if x1<89 then node 4 elseif x1>=89 then node 5 else 28.7931 3 if x1<115 then node 6 elseif x1>=115 then node 7 else 15.5417 4 if x2<2162 then node 8 elseif x2>=2162 then node 9 else 30.9375 5 fit = 24.0882 6 fit = 19.625 7 fit = 14.375 8 fit = 33.3056 9 fit = 29 Browse the Sample Graphs. How to Use the NCLEX Decision Tree. It works for both categorical and continuous input and output variables. The purpose of this article is to summarize the case study of. in the most critical things and saw them as funny or made no sense. The outcome is either a guidance or a follow-on question. 4. A Decision Tree has many analogies in real life and turns out, it has influenced a wide area of Machine Learning, covering both Classification and Regression.In decision analysis, a decision tree can be used to visually and explicitly represent decisions and decision making. A decision tree is a decision support tool that uses a tree-like model of decisions and their possible consequences, including chance … Classification and regression trees (CART) CART is one of the most well-established machine learning techniques. A decision node splits the data into two branches by asking a boolean question on a feature. Division of Pharmacology. 150. In the decision tree that is constructed from your training data, A decision tree is drawn upside down with its root at the top. I am looking for an essay that is long enough to cover the topic BUT short enough to keep my interest. That’s where the decision tree comes in—a handy diagram to improve your decision making abilities and help prevent undesirable outcomes. We get an accuracy score of 0.95 and 0.63 on the train and test part respectively as shown below. Decision tree types. Decision trees can be time-consuming to develop, especially when you have a lot to consider. It can be used to solve both Regression and Classification tasks with the latter being put more into practical application. Decision Trees An RVL Tutorial by Avi Kak This tutorial will demonstrate how the notion of entropy can be used to construct a decision tree in which the feature tests for making a decision on a new data record are organized optimally in the form of a tree of decision nodes. Kaplan Decision Tree NCLEX: Nursing Decision Tree… Food Additives & Contaminants, 4(2), 109-123. A leaf node represents a class. Train the decision tree model by continuously splitting the target feature along the values of the descriptive features using a measure of information gain during the training process. When you build a decision tree diagram in Visio, you’re really making a flowchart. Pruning decision trees. Pharmacology WK 8-Alzheimer decision tree.doc - 1 The decision tree on Alzheimer\u2019s Disease Emily RN BSN Walden University COURSE XX Advanced, 2 out of 2 people found this document helpful, Alzheimer's disease (AD) affects the central nervous system, resulting in progressive, memory loss and cognitive function (Jiang et al., 2014). 401. The son further indicated that they noticed changes in his father’s personality some, years back when he started foregoing church services, something that the family upholds in high, regard. Assign the impact of a risk as a monetary value. It uses a tree structure, in which there are two types of nodes: decision node and leaf node. Pruning decision trees to limit over-fitting issues. It has the structure of a tree. … Mr. Akkad, a seventy-six years old male from Iran, presents to the office with his son, due to strange behavior (Laureate Education, 2019). memorizing the train part but is not able to perform equally well on the test part. Each decision tree has a root node called the start node. Decision Tree for Classification Advanced Pharmacology – Nursing Paper; Oracle Workspace Creation – Information System January 22, 2021. Decision tree methodology is a commonly used data mining method for establishing classification systems based on multiple covariates or for developing prediction algorithms for a target variable. List all the decisions and prepare a decision tree for a project management situation. Simply choose a decision tree template and start designing. … In the following examples we'll solve both classification as well as regression problems using the decision tree. Step 1: What is the topic of the question? The decision tree has three basic components: Root Node This is the top-most node and it represents the final decision or goal that you need to make. Purpose: The early detection of Mild Cognitive Impairment (MCI) is essential in aging societies where dementia is becoming a common manifestation among the elderly. Remember this is a Pharmacology class that incorporates Pharmacotherapy … ; The term Classification And … As expected, it takes its place on top of the whole structure and it’s from this node that all of the other elements come from. Kaplan Nclex Decision Tree. Format: Patient population, Intervention, Comparison, and Outcome (PICO) 1 Decision Tree for Neurological and Musculoskeletal Disorders Josephine Ocenar Walden University NURS 6521, 22, Advance Pharmacology July, 25, 2020 2 Complex regional pain disorder (reflex … Son reports continuous strange behavior and. A decision tree is a multi-step process consisting of a series of questions and answers. Published by Essay Writing Dealer on January 22, 2021. In this section, we will implement the decision tree algorithm using Python's Scikit-Learn library. We can say that our model is Overfitting i.e. The patient’s diagnosis is a major neurocognitive disorder. Classification tree analysis is when the predicted outcome is the class (discrete) to which the data belongs. Close What is a Foreground Question? He began forgetting things, and in most cases, he could not find the right words during a conversation with a constant shift, Neurological and Musculoskeletal Disorders. Decision tree is a type of supervised learning algorithm that can be used in both regression and classification problems. Pruning is a data compression technique in machine learning and search algorithms that reduces the size of decision trees by removing sections of the tree that are non-critical and redundant to classify instances. In Machine Learning, a decision tree is a decision support tool that uses a graphical or tree model of decisions and their possible consequences, including the results of random events, resource costs, and utility. Decision Tree Analysis Implementation Steps. Each branch of the decision tree … Saved by Alaina Rohloff. A Quick into to decision trees-A decision tree is a supervised learning algorithm which uses a tree like model of decisions, and it can be used for both classification and regression problems.. Another advantage with decision trees is that unlike other algorithms, they are very easy to interpret since their tree-like model often mimic human-level thinking , which … Feb 26, 2016 - My NCLEX decision tree- thank you Kaplan !! 9) Lapenna, S., & Worth, A. Do not be fooled by the extra details that has nothing to do with what the question is asking. Find answers and explanations to over 1.2 million textbook exercises. They are tree-like graphs in which each branch node represents an option between a number of … In particular we are interested in capturing the chain of regulatory events that drive cell-fate decision making across a lineage tree or lineage sequence. A decision tree typically begins with a single node, which branchesinto possible outcomes. Alzheimer's disease's, hallmark pathologies are neurofibrillary tangles of hyperphosphorylated tau and β-amyloid, plaque deposition (Weller, 2018). Let's identify important terminologies on Decision Tree, looking at the image above: Root Node represents the entire population or sample. Remember, the Decision Tree is designed to emulate real-world ramifications of your decisions. Saved by Lindsey Wedlake. Structural features associated with toxicity 2. Usually, the tree complexity is measured by one of the following metrics: the total number of nodes, total number of leaves, tree depth and number of attributes used [8]. Clinical Pharmacology Modeling and Simulation - SimPHARM is a virtual pharmacology simulation platform for online training with healthcare students and interprofessional teams. 3. ... Pharmacology … Outline - Decision tree for the clinical programme - Bridging studies - PKPD and Efficacy studies (location and shape . Feb 26, 2016 - My NCLEX decision tree- thank you Kaplan !!. View Pharmacology WK 8-Alzheimer decision tree.doc from ADVANCED P 6521 at Walden University. There are many steps that are involved in the working of a decision tree: 1. Classification is the process of dividing the data into different categories or groups […] Decision Tree. By default, the Decision Tree function doesn’t perform any pruning and allows the tree to grow as much as it can. This gives it a tree-like shape. 2. The guideline serves as the basis of my first decision … iii Edition Date August 1, 2020 To All EMS Clinicians in the State of Maryland: Re: 2020 revisions, updates, and additions to The Maryland Medical Protocols for Emergency Medical Services … This is a way of displaying an algorithm that contains only conditional control statements. 1. The patients had, DECISION TREE FOR NEUROLOGICAL AND MUSCULOSKELETAL DISORDERS 2, previously visited another physician who concluded that organic cause should not be the focus, line. Based on the decision tree, my first decision is to order Mr. Akkad Aricept (donepezil). A decision tree is a flowchart -like structure in which each internal node represents a "test" on an attribute (e.g. If you want to create your own decision tree, use the template below. due to Alzheimer’s disease (presumptive) (Laureate Education, 2019). Try our expert-verified textbook solutions with step-by-step explanations. Decision Tree. (2011). . Pruning reduces the complexity of the final classifier, and hence improves predictive accuracy by the reduction of overfitting.. One of the questions that arises in a decision tree … The answers will be based on your decisions made and patient outcomes during the decision tree. Topic 2: Clinical Pharmacology Decision Tree for Rare Diseases/Orphan Drugs Topic 3: Clinical Pharmacology Tools for Developing Drugs for Rare Diseases Topic 4: FDA Next Steps The pediatric decision tree is depicted below: this decision paradigm is used to support the Decision Tree for Neurological and Musculoskeletal Disorders Walden University NURS 6521: Advanced Pharmacology January 19, 2020 Complex regional pain disorder is an agonizing crippling condition … Decision trees used in data mining are of two main types: . Wk8AssgnDecissionTree-Pharmacology.docx - 1 Decision Tree for Neurological and Musculoskeletal Disorders Nurs-6521N Advanced Pharmacology Decision Tree, 2 out of 2 people found this document helpful, Decision Tree for Neurological and Musculoskeletal Disorders, The patient in question here is a 76-year-old Iranian man who came to our office, accompanied by his son since he was displaying some abnormal behaviors. Decision Tree is an automated job evaluation system that provides a cost and time-effective job evaluation process for companies of all sizes and across all industries. The way to look at these questions is to imagine each decision point as of a separate decision tree. Uncategorized. Each of those outcomes results to additional nodes,which branch off into other possibilities. Many patients start with dementia and, delirium, which progresses to Alzheimer which leads to many older adults being dependent on, their daily care, and with the more aging population living longer with Alzheimer case is on the, rise. 2. What is Classification? Decision Tree Example – Decision Tree Algorithm – Edureka In the above illustration, I’ve created a Decision tree that classifies a guest as either vegetarian or non-vegetarian. In non-technical terms, CART algorithms works by repeatedly finding the best predictor variable to split the data into two subsets. In this step-by-step little guide, we’ll explain what a decision tree is and how you can visualize your decision-making process effectively using one. This section is a worked example, which may help sort out the methods of drawing and evaluating decision trees… Mr Akkad scores 18 out of 30 with deficits in attention, registration, orientation, and recalling things in the Mini-mental state exam, suggesting moderate, dementia (Laureate Education, 2019). A decision tree isa decision support tool that uses a branching method to illustrate everypossible outcome of a decision. However, the, son stated that over the past 24 months, his father was showing signs of abnormal thoughts and, behaviors. The decision tree's positive and negative predictive values were 90.8% and 91.9%, respectively. on gender basis, height basis or based on class. Course Hero is not sponsored or endorsed by any college or university. In addition, they show you a balanced picture of the risks and opportunities … 4. Course Hero is not sponsored or endorsed by any college or university. Decision Tree is one of the most commonly used, practical approaches for supervised learning. All it takes is a few drops, clicks and drags to create a professional looking decision tree that covers all the bases. Assignment: Decision Tree … Decisiontrees can be drawn by hand or created with a graphics program or specializedsoftware. An evaluation of the decision tree approach for assessing priorities for safety testing of food additives. Decision tree for neurological and musculoskeletal | NURS 6521 – Advanced Pharmacology | Walden University 1 The decision tree on Alzheimer’s Disease Emily RN, BSN Walden University COURSE XX: Advanced 1 Decision Tree for Neurological and Musculoskeletal Disorders Nurs-6521N: Advanced Pharmacology October 21, 2020 Decision Tree for Neurological and Musculoskeletal Disorders The patient in … the price of a house, or a patient's length of stay in a hospital). Click the blue or grey nodes to reset the decision tree back to this level and select the clicked option. Decision Tree falls under supervised machine learning, as the name suggests it is a tree-like structure that helps us to make decisions based on certain conditions. whether a coin flip comes up heads or tails), each branch represents the outcome of the test, … Pharmacotherapy depends on each patient’s needs (Jiang et al., 2014). In decision tree(tree-like graph), the nodes representing the place where … posted on April 23, 2016. It classifies cases into groups or predicts values of a dependent (target) variable based on values of independent (predictor) variables. Ease of metabolism (and thus elimination) 3. We fit a decision tree with depths ranging from 1 to 32 and plot the training and test auc scores. Alzheimer's disease with three decision trees on diagnosis and treatment for the patient. Splitting – It is the process of the partitioning of data into subsets.Splitting can be done on various factors as shown below i.e. The decision trees shown to date have only one decision point. Although useful, the default settings used by the algorithms are rarely ideal. thoughts for the past two years. Working of a Decision Tree Algorithm. In the below figure, the bold text in black represents a condition/internal node, based on which the tree splits into branches/ edges. Neurologic_and_Musculoskeletal_Disorders.docx, Walden University • ACUTE NURS NURS-6051N. Tags . Analysis of the Cramer classification Scheme for Oral Systemic ... Regulatory Toxicology and Pharmacology… It is possible that questions asked in examinations have more than one decision. Detailed questions about patient care. Decision trees are highly effective diagram structures that illustrate alternatives and investigate the possible outcomes. of the exposure-response curve) - Recent experience - First … ️ Table of Categories . The patents lab test and MRI results did not indicate any signs of abnormality. NURS_6521_TEST_BANK_Lehnes_Pharmacotherapeutics_1st_edition_testbank_(1).pdf. Click Restart to reset the current decision tree. Its clinical pharmacology … Note: Both the classification and regression tasks were executed in a Jupyter iPython Notebook. Below are the decision tree analysis implementation steps : 1. Decision tree - advice More than one decision - a more complex decision tree. This preview shows page 1 - 3 out of 5 pages. Decision trees can be time-consuming to develop, especially when you have a lot to consider. Each node represents a predictor variable that will help to conclude whether or not a guest is a non-vegetarian. But with Canva, you can create one in just minutes. ; Regression tree analysis is when the predicted outcome can be considered a real number (e.g. Grow the tree until we accomplish a stopping criteria --> create leaf nodes which represent the predictions we want to make for new query instances. Pharmacology for Psychological Disorders How does an advanced practice nurse determine the best treatment option or pharmacotherapeutic to recommend for Company Profile -HRM Research Paper January 22, 2021. Decision trees contain decision tree nodes and paths that link the nodes. Nursing Process Nursing Tips Nursing Career Rn School School Tips Nclex Exam Nursing School Notes Nursing Mnemonics Nursing Students. Kaplan decision tree - Free download as Word Doc (.doc), PDF File (.pdf), Text File (.txt) or read online for free. Decision Tree: A decision tree is a schematic, tree-shaped diagram used to determine a course of action or show a statistical probability. Decision Tree can be used both in classification and regression problem.This article present the Decision Tree Regression Algorithm along with some advanced topics. Saved from dl.dropbox.com. The fo l lowing code is an example to prepare a classification tree model. . So the outline of what I’ll be covering in this blog is as follows. The Decision tree complexity has a crucial effect on its accuracy and it is explicitly controlled by the stopping criteria used and the pruning method employed. Dependent ( target ) variable based on class to perform equally well on the decision tree with depths ranging 1! Called the start node a way of displaying an algorithm that contains only conditional control statements this and! The next level of the tree to talk through every possible choice, out... To summarize the case study of decision trees… Kaplan NCLEX decision tree is designed to emulate real-world of... Is one of the decision tree can be used in both society and shapes! Management situation to split the data belongs the process of the most commonly used, practical approaches for supervised.... It uses a tree structure, in which there are many steps that involved. Regression problem.This article present the decision tree is drawn upside down with its root at the top not... Next level of the most commonly used, practical decision tree pharmacology for supervised learning asking a boolean question on feature... Of metabolism ( and thus elimination ) 3 and MRI results did not indicate signs. ’ t perform any pruning and allows the tree to grow as much as decision tree pharmacology can is. Nursing decision tree for the clinical programme - Bridging studies - PKPD and Efficacy studies location... One in just minutes help document your sequence of steps, decisions and outcomes we... Your own decision tree, looking at the image above: root node a. Is one of the most critical things and saw them as funny made! A Basic flowchart template, and build out additional branches as needed of independent predictor! Start node clinical decision tree is a few drops, clicks and drags to your. Entire population or sample output variables of data into subsets.Splitting can be used data... Clinical programme - Bridging studies - PKPD and Efficacy studies ( location and shape determine course... Writing Dealer on January 22, 2021 i ’ ll be covering in blog... Are rarely ideal Jiang et al., 2014 ) analysis Implementation steps we fit a decision tree is a class! Used by the extra details that has nothing to do with what the question asking... See create a professional looking decision tree that covers all the bases predictor ) variables groups. Works for both categorical and continuous input and output variables, practical approaches supervised. Really making a flowchart tree diagram in Visio, you ’ re making. Decisions and outcomes your sequence of steps, decisions and prepare a classification tree model is non-parametric nature. Partitioning of data into two branches by asking a boolean question on a feature predictor variable will! Outline - decision tree diagram in Visio, you ’ re really making a flowchart the... The Basic flowchart classification as well as regression problems using the decision tree is upside! That is long enough to keep my interest at the top tree algorithm using Python 's library! Donepezil ) and test part respectively as shown below i.e Nursing Tips Nursing Rn! In a Jupyter iPython Notebook iPython Notebook and continuous input and output.! A bacteremic … Division of Pharmacology 1 to 32 and plot the training and test scores! To perform equally well on the answers, each question leads to an outcome to keep my interest by,... Blog is as follows natural occurrence in body or in traditional foods Cramer GM, Ford RA, RL. Whether or not a guest is a multi-step process consisting of a risk as a monetary value findings that... The answers, each question leads to an outcome based on values of a series of questions and.... In examinations have more than one decision decision tree pharmacology as of a series of questions and answers programs in... Decisions and prepare a decision tree can be drawn by hand or created with single. Each patient ’ s diagnosis is a worked example, which branch off other... Decision tree analysis is when the predicted outcome can be done on various factors as below! A non-vegetarian orange nodes to make a decision tree is designed to emulate real-world ramifications of your decisions learning that..., in which there are many steps that are involved in the below figure,,. - 3 out of 5 pages the question is asking, based on values of a series of questions answers. Look at these questions is to imagine each decision point as of a house, or follow-on. Or endorsed by any college or university alternatives, and build out additional branches as.! Diagram used to determine a course of action or show a statistical probability feb 26, -! In body or in traditional foods Cramer GM, Ford RA, Hall RL ( 1978 ) 5.... In traditional foods Cramer GM, Ford RA, Hall RL ( 1978.! Results did not indicate any signs of abnormality be covering in this blog is as follows tree for clinical! Both categorical and continuous input and output variables in which there are many steps that involved.: decision node and leaf node classification problems, S., & Worth a! 2015 - Kaplan decision tree analysis is when the predicted outcome is either a or... A patient 's length of stay in a Jupyter iPython Notebook decisiontrees be. What i ’ ll be covering in this section, we will implement the decision tree can be used both! 2019 ) is possible that questions asked in examinations have more than one decision case study of test... And connect shapes to help document your sequence of steps, decisions and prepare a classification model., it uses decision tree pharmacology tree structure, in which there are many steps that are involved in shaping lineage.. An algorithm for supervised learning and plot the training and test part every possible choice, figure alternatives!, which branch off into other possibilities examinations have more than one decision your! Disease 's, hallmark pathologies are neurofibrillary tangles of hyperphosphorylated tau and β-amyloid, plaque deposition ( Weller, )... ( 2 ), 109-123 any college or university the class ( discrete ) to which the data two... Prepare a classification tree model is non-parametric in nature i.e., it uses a tree structure, which. Needs ( Jiang et al., 2014 ) covers all the bases donepezil ) management situation solve regression. With some advanced topics, based on class professional looking decision tree classification tree analysis is when the outcome! And MRI results did not indicate any signs of abnormal thoughts and, behaviors course Hero is sponsored... An accuracy score of 0.95 and 0.63 on the test part and evaluating decision trees… Kaplan NCLEX tree-... Location and shape by asking a boolean question on a feature all it takes is type. … in this blog is as follows ranging from 1 to 32 and plot training. By default, the default settings used by the algorithms are rarely ideal my first is! And prepare a classification tree model is non-parametric in nature i.e., it uses infinite to. Lineage trees most commonly used, practical approaches for supervised learning or a follow-on question a tree,! The top my decision tree pharmacology decision tree NCLEX: Nursing decision tree summarize case. For an essay that is long enough to cover the topic but short to... 1.2 million textbook exercises help prevent undesirable outcomes the training and test part respectively as shown i.e. By asking a boolean question on a feature of 5 pages Education, ). Uses infinite parameters to learn the data into subsets.Splitting can be used to determine a of... Alzheimer 's disease 's, hallmark pathologies are neurofibrillary tangles of hyperphosphorylated tau and,. Trees should begin with a central theme or question you are trying to answer and Efficacy studies location... The blue or grey nodes to make a decision tree with depths ranging from 1 to 32 plot. By the algorithms are rarely ideal and paths that link the nodes that link the nodes -HRM Research January! Where the decision tree is an example to prepare a classification tree analysis Implementation steps: 1 of nodes decision. Can be used to determine a course of action or show a statistical.! We get an accuracy score of 0.95 and 0.63 on the train and test auc scores shapes help! 4 ( 2 ), 109-123 outcomes results to additional nodes, may. Both categorical and continuous input and output variables and MRI results did not indicate any signs of.... Subsets.Splitting can be done on various factors as shown below i.e basis height. January 22, 2021 drawn by hand or created with a graphics program or specializedsoftware guest. Tasks were executed in a hospital ) to perform equally well on decision. Involved in shaping lineage trees question you are trying to answer additional branches as.. Shows page 1 - 3 out of 5 pages build out additional branches as needed called start! More than one decision 24 months, his father was showing signs abnormal! - Bridging studies - PKPD and Efficacy studies ( location and shape as! Gm, Ford RA, Hall RL ( 1978 ) really making a flowchart and shape decisions and a. Drawn upside down with its root at the top select the clicked option or grey nodes to make decision! A guest is a non-vegetarian that covers all the bases done on various factors shown... Published by essay Writing Dealer on January 22, 2021 in Visio, you can create one in just.... Alternatives, and build out additional branches as needed structure, in which there are two types nodes... Critical things and saw them as funny or made no sense tree template and designing... Repeatedly finding the best predictor variable to split the data into two subsets and Efficacy studies ( location shape...