Version Spaces Learning by managing multiple models Learning
Version Spaces Learning by managing multiple models
Learning by analyzing differences p p Student must learn a concept. How do you propose to teach the concept? Consider the concept of an “Arch”
What make’s an arch p p Teacher can provide examples and counter examples: An arch is made up of n n p Supports Top What are an arch’s properties?
Near-miss improves understanding NOT an ARCH But close Near-miss can add a link System learns “must-support”
Near-miss is a negative example of the concept Negative example can remove (or modify) a link
Positive example can help generalize Arch’s top can be a brick OR a wedge
p Negative Examples allow us to n p Generalize or Specialize? Positive Examples allow us to n Generalize of Specialize?
Version Spaces: Learn by managing multiple models
Version spaces p Each time a general model is specialized, that specialization must be a generalization of an existing specific model. n p Corollary: Each time a specific model is generalized, that generalization must be a specialization of an existing general model Each time a general model is specialized that specialization must not be a specialization of ANOTHER general model
John’s allergies Number Restaurant Meal 1 Sam’s 2 Day Cost Reaction Breakfast Friday Cheap Yes Lobdell’s Lunch Friday Expensive No 3 Sam’s Lunch Saturday Cheap Yes 4 Sarah’s Breakfast Sunday Cheap No 5 Sam’s Breakfast Sunday Expensive No
Version Space [? , ? , ? ] [Sam’s, breakfast, friday, cheap] General Specific
[Lobdell, lunch, Friday, expensive] Negative example: p What happens to “Most general model”? p n n p Cannot be lobdell’s must be Sam’s Cannot be lunch, must be breakfast Cannot be expensive, must be cheap Both samples say Friday, so that feature must not matter What happens to “Most specific model”?
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