Data Mining Application: CART. CART: Binary Recursion Decision Tree program from Salford Systeems www.salford-systems.com 30-day evaluation copy from.

Slides:

Advertisements

Similar presentations

Target Marketing Process: Linking Customer Needs to Marketing Action

Advertisements

Market Research Ms. Roberts 10/12. Definition: The process of obtaining the information needed to make sound marketing decisions.

Collecting Citizen Input Management Learning Laboratories Presentation to Morrisville, NC January 2014.

Huffman code and ID3 Prof. Sin-Min Lee Department of Computer Science.

1 Data Mining Classification Techniques: Decision Trees (BUSINESS INTELLIGENCE) Slides prepared by Elizabeth Anglo, DISCS ADMU.

Discriminant Analysis Database Marketing Instructor:Nanda Kumar.

A Quick Overview By Munir Winkel. What do you know about: 1) decision trees 2) random forests? How could they be used?

Chapter 7 – Classification and Regression Trees

Chapter 7 – Classification and Regression Trees

Data Quality Class 9. Rule Discovery Decision and Classification Trees Association Rules.

1 Spreadsheet Modeling & Decision Analysis: A Practical Introduction to Management Science, 3e by Cliff Ragsdale.

About ISoft … What is Decision Tree? Alice Process … Conclusions Outline.

Learning Decision Trees Brief tutorial by M Werner.

MR2300: MARKETING RESEARCH PAUL TILLEY Unit 10: Basic Data Analysis.

Machine Learning in Real World: CART 2 Outline  CART Overview and Gymtutor Tutorial Example  Splitting Criteria  Handling Missing Values  Pruning.

Version 4 for Windows NEX T. Welcome to SphinxSurvey Version 4,4, the integrated solution for all your survey needs... Question list Questionnaire Design.

Decision Tree Models in Data Mining

Microsoft Enterprise Consortium Data Mining Concepts Introduction to Directed Data Mining: Decision Trees Prepared by David Douglas, University of ArkansasHosted.

Beyond Opportunity; Enterprise Miner Ronalda Koster, Data Analyst.

Introduction to Directed Data Mining: Decision Trees

TURKISH STATISTICAL INSTITUTE INFORMATION TECHNOLOGIES DEPARTMENT (Muscat, Oman) DATA MINING.

 Marketing is the process used to determine what products or services may be of interest to customers, and the strategy to use in sales, communications.

1 Project 7: Huffman Code. 2 Extend the most recent version of the Huffman Code program to include decode information in the binary output file and use.

A Neural Network Approach to Predicting Stock Performance John Piefer ECE/CS 539 Project Presentation.

Biostatistics, statistical software II. A brief survey of statistical program systems Krisztina Boda PhD Department of Medical Informatics, University.

Lesson 7-Creating and Changing Directories. Overview Using directories to create order. Managing files in directories. Using pathnames to manage files.

Building And Interpreting Decision Trees in Enterprise Miner.

McGraw-Hill/Irwin The O’Leary Series © 2002 The McGraw-Hill Companies, Inc. All rights reserved. Microsoft Excel 2002 Lab 4 Using Solver, Linking Workbooks,

1 Commissioned by PAMSA and German Technical Co-Operation National Certificate in Paper & Pulp Manufacturing NQF Level 3 Collect and use data to establish.

Introduction to SPSS Edward A. Greenberg, PhD

Section Market Research & Development

1 Spreadsheet Modeling & Decision Analysis: A Practical Introduction to Management Science, 3e by Cliff Ragsdale.

Chapter 9 – Classification and Regression Trees

Copyright © 2010, SAS Institute Inc. All rights reserved. Applied Analytics Using SAS ® Enterprise Miner™

Zhangxi Lin ISQS Texas Tech University Note: Most slides are from Decision Tree Modeling by SAS Lecture Notes 5 Auxiliary Uses of Trees.

Some working definitions…. ‘Data Mining’ and ‘Knowledge Discovery in Databases’ (KDD) are used interchangeably Data mining = –the discovery of interesting,

Neural Networks Automatic Model Building (Machine Learning) Artificial Intelligence.

Decision Trees. MS Algorithms Decision Trees The basic idea –creating a series of splits, also called nodes, in the tree. The algorithm adds a node to.

WRITING REPORTS Introduction Section 0 Lecture 1 Slide 1 Lecture 6 Slide 1 INTRODUCTION TO Modern Physics PHYX 2710 Fall 2004 Intermediate 3870 Fall 2015.

Week 8: QUANTITATIVE RESEARCH (2) An introduction to using SPSS to summarise & analyse survey data MA CORPORATE SOCIAL RESPONSIBILITY ACP011C – RESEARCH.

Research Uma Kanjilal. Functional Roles of Marketing Research DescriptiveStatements of fact DiagnosticExplanation of data PredictiveUsing data for forecasting.

1 September 7 th – Book check out at 9:25 window 3. Review Expectations Assign seats Attendance Review how to come to class. Writing sample – Slide 2 Get.

1 05 IT.ppt Market and Customer Management - Customer Loyalty 5. Loyalty and Information Technology Frequently asked questions: qWhat is a customer loyalty.

Eco 6380 Predictive Analytics For Economists Spring 2016 Professor Tom Fomby Department of Economics SMU.

BY International School of Engineering {We Are Applied Engineering} Disclaimer: Some of the Images and content have been taken from multiple online sources.

Classification Tree Interaction Detection. Use of decision trees Segmentation Stratification Prediction Data reduction and variable screening Interaction.

Data Resource Management – MGMT An overview of where we are right now SQL Developer OLAP CUBE 1 Sales Cube Data Warehouse Denormalized Historical.

MKT 435 RANK PRIDE IN EXCELLENCE/MKT435RANKDOTCOM.

MKT 230 Week 9 Final Project Marketing Plan To purchase this material click below link 230-Week-9-Final-Project-Marketing-Plan.

MKT 450 Week 3 Learning Team Assignment Detailed International Marketing Plan Outline Part I To purchase this material click below link

HCS 465 Week 4 Individual Evaluating the Research Process To purchase this material click below link

ACC 542 Week 5 Learning Team Assignment Audit Proposal To purchase this material click below link

If I would have know then…

MKT 435 MENTOR Educational Resources / mkt435mentor.com

MKT 435 Competitive Success-- snaptutorial.com

MKT 435 Education for Service-- snaptutorial.com.

MKT 435Competitive Success/tutorialrank.com

MKT 435 Education for Service-- snaptutorial.com

MKT 435 Education for Service-- tutorialrank.com.

MKT 435 MENTOR Lessons in Excellence -- mkt435mentor.com.

MKT 435 Teaching Effectively-- snaptutorial.com

MKT 435 Teaching Effectively-- snaptutorial.com

MKT 435 MENTOR Education for Service--mkt435mentor.com.

MKT 435 Education for Service-- tutorialrank.com

MKT 440 Education for Service-- tutorialrank.com

Tabulations and Statistics

Data Mining for Business Analytics

CSCI N207 Data Analysis Using Spreadsheet

Computer Science Transition Work Code Skills Demonstration

MKT 435 MENTOR best future education / mkt435mentor.com.

Presentation transcript:

Data Mining Application: CART

CART: Binary Recursion Decision Tree program from Salford Systeems 30-day evaluation copy from – –Company: Villanova University –Department: Computer Sciences

CART Binary Recursive Trees One target variable Splits data into a number of classes on the target variable (set-able input parameter) Many predictor variables At each recursion CART determines one yes-no (binary) question based on one predictor variable Various splitting criteria. Default (GINI) measures how well rule separates classes in parent node

CART Tutorial We have defined three market segments, numbered 1, 2, 3. They represent “profitability”, broadly defined as “how much money did we make from this person in the last year”. We are interested in questions which distinguish these segments so we know how to better target future marketing.

CART Gym Data Tutorial: Variables SEGMENT Member's market segment (coded 1,2,or 3) ANYRAQT Racquet ball usage (binary indicator coded 0, 1) TANNING Number of visits to tanning salon PERSTRN Personal trainer (binary indicator coded 0, 1) ONAER Number of on-peak aerobics classes attended OFFAER Number of off-peak aerobics classes attended ANYPOOL Pool usage (binary indicator coded 0, 1) CLASSES Number of classes taken NSUPPS Number of supplements/vitamins/frozen dinners purchased SMALLBUS Small business discount (binary indicator coded 0, 1) OFFER Terms of offer FIT Fitness score NFAMMEN Number of family members HOME Home ownership (binary indicator coded 0, 1)

Potential Data Sources CART uses data in the Systat for Windows format, extension.syd. (Systat is a very popular statistical package) The downloaded version includes a dynamic link to a program called DMBS-copy, which also allows you to use other data formats such as ASCII, Excel, etc.

Summary: CART Good for generating decision trees, and provides a lot of alternatives and a lot of information. Can also use the rules created and the resulting data as input into additional tools Far more information there than you want to look at if you don’t know what you’re looking for.

CART Assignment: Three pieces: –Download and install it –Work through the tutorial yourself and do a brief report. –Analyze a new set of data and answer some questions about it. I am in the process of getting descriptions for the sample data in the download and will prepare questions based on one of those Or if you have data in an appropriate format you may use your own data and questions.