week 1 introduction presentation

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extension.uci.edu

Effective Data Preparation

Week 1: Introduction

Data integration used to be done solely in data warehousing

operations. Now, predictive analysts must do it themselves,

to make sure that it is done right!


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Introduction

Assigned Readings for all students

Introductions by other students

Grading Rubric document

Preface, Introduction, and Chapter 1 in the text

Assigned Readings for students without SDM

(STATISTICA Data Miner)

Procedure for downloading and installing SDM

Inserting and Connecting Nodes document

SDM Help topic on the SDM interface

Chapter 10 in the text

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Getting Acquainted & Oriented

Welcome to Effective Data Preparation!

This course will be presented in the form of an

extended tutorial for preparing and modeling

the KDD-Cup 1998 data set.

Each week will have 2- 3 assignments to be completed.

Most assignments will be file submissions

Work for a given week will require up to 15 hours of work. There will be several quizzes.

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Getting Acquainted & Oriented

Get acquainted with other students. Learn

where they work, and what their goals are.

If you have not done so before, read the

documents on downloading and installing

SDM, and the document on connecting SDM

Become familiar with the Grading Rubric

document, so you will know what to expect in

this class.

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Getting to Know Everyone

Introduce yourself in the Welcome Messages

Forum

Respond to at least one welcome message by

a student. This assignment will be graded as a

pass/fail task.

You can help each other with the tasks in this

course. Relationships are important!

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STATISTICA Data Miner We will be the same STATISTICA Data Miner (SDM) Version 12

software package from Statsoft, which was used in the Intro

course.

If you have not done so before (or have to do it again), read

the document:

PROCEDURE_for_DOWNLOADING_STATISTICA_Data_Miner_software.doc

Download and install Version 12 of SDM

If you have question about or problems with the download

and installation, contact [email protected]

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mailto:[email protected]:[email protected]


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A New Look for STATISTICA

If you used SDM Version 10 in one of the previous

Introduction courses, you will notice a big change in

the modeling canvas

Version 10 divided the canvas into 4 parts

Version 12 has no divisions on the canvas

This means you can put your modeling icons anywhere you

want to!

I am a big fan of this change.

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Become Familiar with SDM

1. Read Data Miner Workspace document in the SDM

Help File

Click on Help on the top menu

Click the Index tab, and enter Data MinerWorkspace

Scroll down to the Data Miner Workspace

document, and read it. Read Chapter 10 (pages 214-234) in the text

about STATISTICA Data Miner.

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Become Familiar with SDM

2. Read the document: Inserting and

Connecting Nodes.doc

3. Become familiar with the SDM Help file.

This facility is a marvelous way to learn about

almost anything related to predictive

analytics in general, and SDM in particular.

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The 10 Steps of Data Preparation

1. Data access and extraction

2. Data Integration

3. Data Cleansing

4. Data conditioning5. Missing value imputation

6. New Variable derivation

7. Variable Selection

8. Algorithm selection

9. Preliminary model building

10. Feedback to earlier data preparation activities

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Modeling:

(in a data preparation course?) Role of modeling in data preparation.

Additional tasks?

An iterative loop!

Practice in model building will be useful in general.

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Is All of this Stuff Necessary?

You will be tempted to omit a step

This is nota good idea

You can create a model without all steps, but

The bottom line is

The motto of Seal Team 6 is: The more blood, sweat and

tears your put into training, the less you will shed in battle

The same is true with data preparation.

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Finished!

That is all that there is in Week 1.

There will be more to do in Week 2, and

particularly in Week 3; the work is not linearly

distributed across all weeks.

You may take the Week 1 test now.

When you finish the test, you can continue to

Week 2 assignments.

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week 1 introduction presentation

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