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.
- Knowledge of your business requirements
- Required: IBM SPSS Modeler Foundations (V18.2) course (0A069G/0E069G) or equivalent knowledge of how to import, explore, and prepare data with IBM SPSS Modeler v18.2, and know the basics of modeling.
- Recommended: Introduction to Machine Learning Models Using IBM SPSS Modeler (V18.2) course (0A079G/0E079G), or equivalent knowledge or experience with the product about supervised machine learning models (CHAID, C&R Tree, Regression, Random Trees, Neural Net, XGBoost), unsupervised machine learning models (TwoStep Cluster), and association machine learning models such as APriori.
Introduction to advanced machine learning models
• Taxonomy of models
• Overview of supervised models
• Overview of models to create natural groupings
Group fields: Factor Analysis and Principal Component Analysis
• Factor Analysis basics
• Principal Components basics
• Assumptions of Factor Analysis
• Key issues in Factor Analysis
• Improve the interpretability
• Factor and component scores
Predict targets with Nearest Neighbor Analysis
• Nearest Neighbor Analysis basics
• Key issues in Nearest Neighbor Analysis
• Assess model fit
Explore advanced supervised models
• Support Vector Machines basics
• Random Trees basics
• XGBoost basics
Introduction to Generalized Linear Models
• Generalized Linear Models
• Available distributions
• Available link functions
Combine supervised models
• Combine models with the Ensemble node
• Identify ensemble methods for categorical targets
• Identify ensemble methods for flag targets
• Identify ensemble methods for continuous targets
• Meta-level modeling
Use external machine learning models
• IBM SPSS Modeler Extension nodes
• Use external machine learning programs in IBM SPSS Modeler
Analyze text data
• Text Mining and Data Science
• Text Mining applications
• Modeling with text data
Frequently asked questionsSee all of our FAQs
How can I create an account on myQA.com?
There are a number of ways to create an account. If you are a self-funder, simply select the "Create account" option on the login page.
If you have been booked onto a course by your company, you will receive a confirmation email. From this email, select "Sign into myQA" and you will be taken to the "Create account" page. Complete all of the details and select "Create account".
If you have the booking number you can also go here and select the "I have a booking number" option. Enter the booking reference and your surname. If the details match, you will be taken to the "Create account" page from where you can enter your details and confirm your account.
Find more answers to frequently asked questions in our FAQs: Bookings & Cancellations page.
How do QA’s virtual classroom courses work?
Our virtual classroom courses allow you to access award-winning classroom training, without leaving your home or office. Our learning professionals are specially trained on how to interact with remote attendees and our remote labs ensure all participants can take part in hands-on exercises wherever they are.
We use the WebEx video conferencing platform by Cisco. Before you book, check that you meet the WebEx system requirements and run a test meeting (more details in the link below) to ensure the software is compatible with your firewall settings. If it doesn’t work, try adjusting your settings or contact your IT department about permitting the website.
Learn more about our Virtual Classrooms.
How do QA’s online courses work?
QA online courses, also commonly known as distance learning courses or elearning courses, take the form of interactive software designed for individual learning, but you will also have access to full support from our subject-matter experts for the duration of your course. When you book a QA online learning course you will receive immediate access to it through our e-learning platform and you can start to learn straight away, from any compatible device. Access to the online learning platform is valid for one year from the booking date.
All courses are built around case studies and presented in an engaging format, which includes storytelling elements, video, audio and humour. Every case study is supported by sample documents and a collection of Knowledge Nuggets that provide more in-depth detail on the wider processes.
Learn more about QA’s online courses.
When will I receive my joining instructions?
Joining instructions for QA courses are sent two weeks prior to the course start date, or immediately if the booking is confirmed within this timeframe. For course bookings made via QA but delivered by a third-party supplier, joining instructions are sent to attendees prior to the training course, but timescales vary depending on each supplier’s terms. Read more FAQs.
When will I receive my certificate?
Certificates of Achievement are issued at the end the course, either as a hard copy or via email. Read more here.