IBM 0A038G - Advanced Predictive Modeling Using IBM SPSS Modeler (v18.1.1) - Seminar / Kurs von PROKODA GmbH

Inhalte

Course Outline

1. Preparing data for modeling· Address general data quality issues· Handle anomalies· Select important predictors· Partition the data to better evaluate models· Balance the data to build better models2. Reducing data with PCA/Factor· Explain the idea behind PCA/Factor· Determine the number of components/factors· Explain the principle of rotating a solution3. Creating rulesets for flag targets with Decision List· Explain how Decision List builds a ruleset· Use Decision List interactively· Create rulesets directly with Decision List4. Exploring advanced supervised models· Explain the principles of Support Vector Machine (SVM)· Explain the principles of Random Trees· Explain the principles of XGBoost5. Combining models· Use the Ensemble node to combine model predictions· Improve model performance by meta-level modeling6. Finding the best supervised model· Use the Auto Classifier node to find the best model for categorical targets· Use the Auto Numeric node to find the best model for continuous targets

Objective

1: Preparing data for modeling · Address general data quality issues · Handle anomalies · Select important predictors · Partition the data to better evaluate models · Balance the data to build better models

2: Reducing data with PCA/Factor · Explain the idea behind PCA/Factor · Determine the number of components/factors · Explain the principle of rotating a solution

3: Creating rulesets for flag targets with Decision List · Explain how Decision List builds a ruleset · Use Decision List interactively · Create rulesets directly with Decision List

4: Exploring advanced supervised models · Explain the principles of Support Vector Machine (SVM) · Explain the principles of Random Trees · Explain the principles of XGBoost

5: Combining models · Use the Ensemble node to combine model predictions · Improve model performance by meta-level modeling

6: Finding the best supervised model · Use the Auto Classifier node to find the best model for categorical targets · Use the Auto Numeric node to find the best model for continuous targets

Hinweise

Unterrichtsmethode

presentation, discussion, hands-on exercises

Dieses Training bieten wir in Kooperation mit der Integrata AG an.

Zielgruppen

· Business Analysts · Data Scientists · Users of IBM SPSS Modeler responsible for building predictive models

Termine und Orte

Datum Uhrzeit Dauer Preis
Hamburg, DE
25.11.2020 09:00 - 16:00 Uhr 8 h Jetzt buchen ›
Leinfelden-Echterdingen, DE
25.11.2020 09:00 - 16:00 Uhr 8 h Jetzt buchen ›

SG-Seminar-Nr.: 5505829

Termine

  • 25.11.2020

    Hamburg, DE

    Leinfelden-Echterdingen, DE

Preise inkl. MwSt. Es können Gebühren anfallen. Für eine exakte Preisauskunft wählen Sie bitte einen Termin aus.

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Datum Uhrzeit Dauer Preis
Hamburg, DE
25.11.2020 09:00 - 16:00 Uhr 8 h Jetzt buchen ›
Leinfelden-Echterdingen, DE
25.11.2020 09:00 - 16:00 Uhr 8 h Jetzt buchen ›