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
Summary
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
Summary
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
Summary
Cleaning and Selecting Data
Selecting cases
Expression Builder
Sorting cases
Identifying and removing duplicate cases
Reclassifying categorical values
Summary
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
Summary
Deriving New Fields
Derive – Formula
Derive – Flag
Derive – Nominal
Derive – Conditional
Summary
Looking for Relationships Between Fields
Relationships between categorical fields
Distribution node
Matrix node
Relationships between categorical and continuous fields
Histogram node
Means node
Relationships between continuous fields
Plot node
Statistics node
Summary
Introduction to Modeling Options in IBM SPSS Modeler
Classification
Categorical targets
Numeric targets
The Auto nodes
Data reduction modeling nodes
Association
Segmentation
Choosing between models
Summary
Decision Tree Models
Decision tree theory
CHAID theory
How CHAID processes different types of input variables
Stopping rules
Building a CHAID Model
Partition node
Overfitting
CHAID dialog options
CHAID results
Summary
Model Assessment and Scoring
Contrasting model assessment with the Evaluation phase
Model assessment using the Analysis node
Modifying CHAID settings
Model comparison using the Analysis node
Model assessment and comparison using the Evaluation node
Scoring new data
Exporting predictions
Summary
更新时间：2021-07-02 20:05:09
完结共137章
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