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Introduction to IBM SPSS Modeler and Data Mining (V16) (0A005G)

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Detaillierter Kursinhalt

Introduction to Data Mining

  • List two applications of data mining
  • Explain the stages of the CRISP-DM process model
  • Describe successful data-mining projects and the reasons why projects fail
  • Describe the skills needed for data mining

Working with Modeler

  • Describe the MODELER user-interface
  • Work with nodes
  • Run a stream or a part of a stream
  • Open and save a stream
  • Use the online Help

A Data-Mining Tour

  • Explain the basic framework of a data-mining project
  • Build a model
  • Deploy a model

Collecting Initial Data

  • Explain the concepts data structure, unit of analysis, field storage and field measurement level
  • Import Microsoft Excel files
  • Import IBM SPSS Statistics files
  • Import text files
  • Import from databases
  • Export data to various formats

Understanding your Data

  • Audit the data
  • Explain how to check for invalid values
  • Take action for invalid values
  • Explain how to define blanks

Setting the Unit of Analysis

  • Set the unit of analysis by removing duplicate records
  • Set the unit of analysis by aggregating records
  • Set the unit of analysis by expanding a categorical field into a series of flag fields

Integrating Data

  • Integrate data by appending records from multiple datasets
  • Integrate data by merging fields from multiple datasets
  • Sample records

Deriving and Reclassifying Fields

  • Use the Control Language for Expression Manipulation (CLEM)
  • Derive new fields
  • Reclassify field values

Looking for Relationships

  • Examine the relationship between two categorical fields
  • Examine the relationship between a categorical field and a continuous field
  • Examine the relationship between two continuous fields

Introduction to Modeling

  • List three modeling objectives
  • Use a classification model
  • Use a segmentation model