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Advanced Data Preparation Using IBM SPSS Modeler

 

Overview

This one day course covers advanced topics to aid in the preparation of data for a successful data mining project. You will learn how to use functions, deal with missing values, use advanced field operations, handle sequence data, apply advanced sampling methods, and improve efficiency.

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Prerequisites

Follow-on Courses

Key Topics

Using Functions

  • Use date functions
  • Use conversion functions
  • Use string functions
  • Use statistical functions
  • Use missing value functions

Data Transformations

  • Use the Filler node to replace values
  • Use the Binning node to recode continuous fields
  • Use the Transform node to change a field’s distribution

Working with Sequence Data

  • Use cross-record functions
  • Use the Count mode in the Derive node
  • Use the Restructure node to expand a continuous field into a series of continuous fields
  • Use the Space-Time-Boxes node to work with geospatial and time data

Sampling Records

  • Use the Sample node to draw simple and complex samples
  • Draw complex samples
  • Partition the data into a training and a testing set
  • Reduce or boost the number of records

Improving Efficiency

  • Use database scalability by SQL pushback
  • Use the Data Audit node to process outliers and missing values
  • Use the Set Globals node
  • Use parameters
  • Use looping and conditional execution

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