课程: Advanced Predictive Modeling: Mastering Ensembles and Metamodeling
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What you should know - SPSS教程
课程: Advanced Predictive Modeling: Mastering Ensembles and Metamodeling
What you should know
- [Instructor] This course is very nearly a sequel to my course in the library, Machine Learning and AI Foundations: Classification Modeling. We'll be mentioning famous algorithms throughout the course, so I'll assume that you're familiar with them. Another topic that's terribly important, trained test partitioning. This is perhaps the most important one on the list. In machine learning, we nearly always divide our data randomly into at least partitions. You're going to want to understand why this is done and how this is done. The classification course covers this well. We'll also be mentioning linear regression quite frequently. It's fundamental to many techniques, and we will be creating ensembles using value estimation approaches, including linear regression itself. Another topic is decision trees. It will come up in many of the videos. So often, that if you plan on taking a course dedicated to trees, it might not be a bad idea to take it first. I have both a basic one and a more…
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