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Advanced Machine Learning Models Using IBM SPSS Modeler (V18.2)

This course presents advanced models available in IBM SPSS Modeler. The participant is first introduced to a technique named PCA/Factor, to reduce the number of fields to a number of core factors, referred to as components or factors. The next topics focus on supervised models, including Support Vector Machines, Random Trees, and XGBoost. Methods are reviewed on how to analyze text data, combine individual models into a single model, and how to enhance the power of IBM SPSS Modeler by adding external models, developed in Python or R, to the Modeling palette.

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    Self paced electronic learning

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    Learning that is virtual

7 courses found

    • Delivery Format: Virtual Learning
    • Date 21 July, 2024
    • Location: Virtual
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    • Delivery Format: Virtual Learning
    • Date 29 July, 2024
    • Location: Virtual
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    • Delivery Format: Virtual Learning
    • Date 20 October, 2024
    • Location: Virtual
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    • Delivery Format: Virtual Learning
    • Date 28 October, 2024
    • Location: Virtual
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    • Delivery Format: Virtual Learning
    • Date 15 December, 2024
    • Location: Virtual
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