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Machine Learning: Summary Greg Grudic CSCI-4830
What is Machine Learning? ,[object Object],[object Object]
A Generic System Input Variables: Hidden Variables: Output Variables: System … …
Another Definition of Machine Learning ,[object Object],[object Object],[object Object]
When are ML algorithms NOT needed? ,[object Object],[object Object]
The Sub-Fields of ML ,[object Object],[object Object],[object Object]
Supervised Learning ,[object Object],[object Object],[object Object],[object Object]
Supervised Learning Algorithms ,[object Object],[object Object]
1-R (A Decision Tree Stump) ,[object Object],[object Object],[object Object],[object Object],[object Object]
Naïve Bayes ,[object Object],[object Object],[object Object],[object Object],[object Object]
Linear Regression ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Linear Regression (Continued) Linearly Separable Not Linearly Separable
Decision Trees ,[object Object],[object Object],[object Object],[object Object]
Neural Networks ,[object Object],[object Object],[object Object],[object Object]
Neural Networks (Continued)
Neural Networks (Continued) ,[object Object]
K Nearest Neighbor ,[object Object],[object Object],[object Object],[object Object],Classify according to Nearest Neighbor Separates the input space
Bagging ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Bagging (continued) ,[object Object],[object Object],[object Object],[object Object]
Boosting ,[object Object],[object Object],[object Object],[object Object]
Boosting (Continued) ,[object Object],[object Object],[object Object]
 
Support Vector Machines ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Linear Support Vector Machines Support Vectors
Nonlinear Support Vector Machines ,[object Object]
Competing Philosophies in Supervised Learning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Competing Philosophies in Supervised Learning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Evaluating Models ,[object Object],[object Object],[object Object],[object Object],[object Object]
Boostrap Estimate
Reinforcement Learning (RL) ,[object Object],[object Object],[object Object]
Q Learning
Agent’s Learning Task
Unsupervised Learning ,[object Object],[object Object],[object Object]
Expectation Maximization (EM) Algorithm ,[object Object],[object Object],[object Object]

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Summary.ppt