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IBM SPSS Modeler: Modeler’s New R Nodes
Rating: 3.2 out of 5(9 ratings)
169 students
Created bySandy Midili
Last updated 5/2014
English

What you'll learn

  • Describe the new features and why they are useful
  • Learn more R through self study
  • Add new graphics capability in Modeler
  • Add new statistics capability in Modeler

Course content

1 section • 20 lectures • 2h 29m total length

  • The Organization of the Seminar3:47
  • Overview of the R Integration Package11:56

    Learn to integrate R with IBM SPSS Modeler using modular data, modeler data, and a model object to build and score predictions.

  • Application Example- A Weather ‘Source Node’2:00
  • Writing the R Code to do GeoCoding in Modeler11:04
  • Building your own Custom R Node7:09
  • Building your own Modeling Node- Random Forests8:10
  • The R model building syntax6:32
  • The R scoring syntax3:13
  • Reviewing the Model Results1:47
  • Building a Dialog for Random Forests12:01

    Build a random forest dialogue in IBM SPSS Modeler, selecting target and predictors, with a default 300 trees, using the custom dialog builder and care package to explore other models.

  • Does Modeler treat an R Model like any other Model2:28
  • String Distance Demonstration6:37
  • Iterative Neural Net Forecasts Demontration3:34
  • Questions about Writing the Neural Net Forecast Node7:46
  • Getting Started with R and Modeler19:41
  • Getting familiar with R using R Studio7:01

    Get familiar with R Studio by starting a new R script, using the console, and exploring the global environment, memory, and vectors; install packages and use help for basic prototyping.

  • Basic Grammar and Commands in R9:59

    Demonstrates basic grammar and commands in R, teaching simple assignment, vector operations, and arithmetic, and showing how to compute mean, standard deviation, and elementwise operations.

  • Matrices, Data Frames, and Models9:20

    Explore matrices and data frames, from creating a 3x3 matrix and previewing the iris dataset with head to converting data files into data frames and building models with lm.

  • Summary Statistics and GGPlot210:27
  • Cbind() and Apply()4:37

Requirements

  • Knowledge or experience with IBM SPSS Modeler or completion of an introductory level data mining course and on the job data mining experience.

Description

IBM SPSS Modeler is a data mining workbench that allows you to build predictive models quickly and intuitively without programming. Analysts typically use SPSS Modeler to analyze data by mining historical data and then deploying models to generate predictions for recent (or even real-time) data.

Overview: Modeler's New R Nodes is a series of self-paced videos. This course is divided into four parts:

    ·What are the new Modeler R Nodes and why are they an exciting addition?

    ·What is R and what are some of the best ways to learn more about it?

    ·Adding new graphics capability with R

    ·Adding new statistics capability with R

We discuss one of the exiting new features of Modeler 16. We show some R functionality in the R environment itself, but the seminar will culminate in the demonstration of R capabilites in a Modeler stream. Advice will be given on how best to develop more skills in this area, but you will have some working knowledge from these videos alone.

Who this course is for:

  • Anyone that has experience with IBM SPSS Modeler or has completed an introductory level data mining course and would like to learn how to use Modeler and R together.

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