更新时间：2021-07-02 20:05:09
封面
版权信息
Credits
About the Authors
About the Reviewer
www.PacktPub.com
Why subscribe?
Customer Feedback
Dedication
Preface
What this book covers
What you need for this book
Who this book is for
Conventions
Reader feedback
Customer support
Downloading the example code
Downloading the color images of this book
Errata
Piracy
Questions
Introduction to Data Mining and Predictive Analytics
Introduction to data mining
CRISP-DM overview
Business Understanding
Data Understanding
Data Preparation
Modeling
Evaluation
Deployment
Learning more about CRISP-DM
The data mining process (as a case study)
Summary
The Basics of Using IBM SPSS Modeler
Introducing the Modeler graphic user interface
Stream canvas
Palettes
Modeler menus
Toolbar
Manager tabs
Project window
Building streams
Mouse buttons
Adding nodes
Editing nodes
Deleting nodes
Building a stream
Connecting nodes
Deleting connections
Modeler stream rules
Help options
Help menu
Dialog help
Importing Data into Modeler
Data structure
Var. File source node
Var. File source node File tab
Var. File source node Data tab
Var. File source node Filter tab
Var. File source node Types tab
Var. File source node Annotations tab
Viewing data
Excel source node
Database source node
Levels of measurement and roles
Data Quality and Exploration
Data Audit node options
Data Audit node results
The Quality tab
Missing data
Ways to address missing data
Defining missing values in the Type node
Imputing missing values with the Data Audit node
Cleaning and Selecting Data
Selecting cases
Expression Builder
Sorting cases
Identifying and removing duplicate cases
Reclassifying categorical values
Combining Data Files
Combining data files with the Append node
Removing fields with the Filter node
Combining data files with the Merge node
The Filter tab
The Optimization tab
Deriving New Fields
Derive – Formula
Derive – Flag
Derive – Nominal
Derive – Conditional
Looking for Relationships Between Fields
Relationships between categorical fields
Distribution node
Matrix node
