目錄(137章)
倒序
- 封面
- 版權(quán)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 更新時(shí)間：2021-07-02 20:05:09
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