Lynda - Machine Learning: Advanced Decision Trees
Lynda - Machine Learning: Advanced Decision Trees
Size: 190 MB | Duration: 1h 16m | Video: AVC (.mp4) 1280x720 15&30fps | Audio: AAC 48KHz 2ch
Genre: eLearning | Level: Advanced | Language: English
Size: 190 MB | Duration: 1h 16m | Video: AVC (.mp4) 1280x720 15&30fps | Audio: AAC 48KHz 2ch
Genre: eLearning | Level: Advanced | Language: English
If you're working towards an understanding of machine learning, it's important to know how to work with decision trees. In this course, explore advanced concepts and details of decision tree algorithms. Learn about the QUEST algorithm and how it handles nominal variables, ordinal and continuous variables, and missing data. Explore the C5. 0 algorithm and review some of its key features such as global pruning and winnowing. Plus, dive into a few advanced topics that apply to all decision trees, such as boosting and bagging.
* Understanding QUEST functions and applications
* C5.0 concepts and practical applications
* Understanding information gain
* Random forests
* Boosting and bagging
* Costs and priors
* C5.0 concepts and practical applications
* Understanding information gain
* Random forests
* Boosting and bagging
* Costs and priors
Lynda - Machine Learning: Advanced Decision Trees
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