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Kursbeskrivning: Clustering and Association Models with IBM SPSS Modeler - ILO

Kursen har inget datum. Ring vår kursbokning 077 186 10 37 för information om en privat utbildning.

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  • Förkunskaper
  • Mål
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Kurskod 0F042SE Leveranstyp Instructor Led - Online Training
(Hands-on labs)
Kurslängd 1.0 dagar Kurstyp
Listpris SEK 7 500,00 exkl moms
SEK 9 375,00 inkl moms
   

NOTE: This is a live, instructor-led online course. Do not make arrangements to travel.

IBM SPSS Education is pleased to offer you our courses in an exciting learning format, Instructor-led Online (ILO). You are offered a similar experience to live classroom training, with the convenience of having it delivered directly to their desktop.

This course demonstrates how to segment or cluster data with all the clustering techniques available in PASW Modeler. The course also provides examples of creating association models to find rules describing the relationships among a set of items, and of creating sequence models to find rules describing the relationships over time among a set of items.

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Målgrupp

This course follows the Introduction to PASW Modeler and Data Mining course or the Advanced Data Preparation with PASW Modeler and is designed for anyone who wishes to become familiar with the full range of modeling techniques available in PASW Modeler to segment (cluster) data and to create models with association or sequence data. For people wishing to successfully build such models using PASW Modeler, this course is an essential part of the learning process.

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Förkunskaper

You should have:

  • General computer literacy
  • Experience using PASW Modeler, including familiarity with the PASW Modeler environment, creating streams, reading in data files, assessing data quality and handling missing data (including the Type and Data Audit nodes), basic data manipulation (including the Derive and Select nodes), and creation of models
  • Prior completion of the Introduction to PASW Modeler and Data

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Mål

Please refer to course overview.

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Nyckelområden

  • Introduction to models for clustering and association
  • Preparing data for modeling
  • Clustering models
  • Association models
  • Sequence models

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