Introduction to Learning – II | Artificial Intelligence | Video lecture

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 Introduction to Learning РII



Artificial Intelligence1:25
Instructional Objectives
Machine learning for classification
Sudeshna Sarkar
Machine learning for classification
Concept learning problem
Hypothesis or model selection
Concept Learning as Search
Some Definitions
False positive and false negative
Inductive Learning Hypothesis
Inductive Bias
Inductive Inference Theory
Current Best Hypothesis Search
Least Commitment Search
Version Space
Version Spaces
Version Space
List-Then Eliminate Algorithm
A Version Space
Choosing the best hypothesis
Displaying the Performance of a Learner
Fitting hypotheses to the training data
An example of an error function
The problem of overfitting
k-fold Cross-validation
Questions for Lecture 33


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