From the course: Machine Learning and AI: Advanced Decision Trees with SPSS

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Ensembles

Ensembles

From the course: Machine Learning and AI: Advanced Decision Trees with SPSS

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Ensembles

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- [Instructor] Now I'd like to introduce a very powerful topic: the whole notion of ensembles. To help me explain it, I want to open a stream that I've built just for this purpose. There's a stream called Ensemble stream. I've added a number of nodes and connections to this stream to facilitate the demonstration, but as long as you double check the source node to verify that the data is where the source node expects it to be, you should be all set. So what's the basic notion of an ensemble? It's more than one model working together to build the predictions. In this case, I've chosen a C5 model and a neural net model. There is a phrase that is sometimes used for this kind of ensemble. This is a heterogeneous ensemble, because we have two different types of models, working together. A common example of a homogeneous model would be many, many C5s working together to make a prediction, something that's often called bagging. So why have I chosen these particular models for my heterogeneous…

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