This course provides an introduction to supervised models, unsupervised models, and association models. This is an application-oriented course and examples include predicting whether customers cancel their subscription, predicting property values, segment customers based on usage, and market basket analysis.
Introduction to machine learning models
Build and apply models in IBM SPSS Modeler
Treatment of missing values
Evaluation measures for continuous targets
Association models: Sequence detection
Supervised models: Black box models - Neural networks
Supervised models: Black box models - Ensemble models
Ensemble the best models
Unsupervised models: K-Means and Kohonen
Treatment of missing values in Kohonen
Unsupervised models: TwoStep and Anomaly detection
Preparing data for modeling
Balance the data
If you need training for 3 or more people, you should ask us about onsite training. Putting aside the obvious location benefit, content can be customised to better meet your business objectives and more can be covered than in a public classroom. It's a cost effective option.
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ITILv3, RESILIA, PRINCE2, PRINCE2 Agile, AgileSHIFT, MSP, M_o_R, P3M3, P3O, MoP, MoV courses on this page are offered by QA Affiliate of AXELOS Limited. ITIL, RESILIA, PRINCE2, PRINCE2 Agile, AgileSHIFT, MSP, M_o_R, P3M3, P3O,MoP, MoV are registered trademarks of AXELOS Limited. All rights reserved.