
Learning: Support Vector Machines
49:34Learning: Boosting Algorithms
51:40Learning: Near Misses and Felicity Conditions in AI
46:54Learning: Sparse Spaces and Phonological Generalization
47:49Genetic Algorithms: MIT Artificial Intelligence
47:16Deep Neural Networks: MIT Artificial Intelligence
49:06Neural Networks and Backpropagation
50:43Learning: Identification Trees and Disorder
49:37Explore the construction of identification trees and the concept of disorder as a metric for building robust classification models, from MIT's AI curriculum.
MIT 6.034 Artificial Intelligence, Fall 2010
In this lecture, we build an identification tree based on yes/no tests. We start by arranging the tree based on tests that result in homogeneous subsets. For larger datasets, this is generalized by measuring the disorder of subsets.
Neural Networks and Backpropagation
Final session in this series