Concept Learning

App is hosted at this link

Find S

1. Initialize h to the most specific hypothesis in H
2. For each positive training instance x
   • For each attribute constraint ai in h
     • If the constraint ai in h is satisfied by x
     • Then do nothing
     • Else replace ai in h by the next more general constraint that is satisfied by x
3. Output hypothesis h

Candidate Elimination

G <- maximally general hypotheses in H

S <- maximally specific hypotheses in H

For each training example d, do

• If d is a positive example
  • Remove from Gany hypothesis inconsistent with d
  • For each hypothesis s in S that is not consistent with d
    • Remove s from S
    • Add toSall minimal generalizations h of s such that
      1. h is consistent with d, and
      2. some member of G is more general than h
    • Remove from S any hypothesis that is more general than another hypothesis in S
• If d is a negative example
  • Remove from S any hypothesis inconsistent with d
  • For each hypothesis g in Gthat is not consistent with d
    • Remove g from G
    • Add to G all minimal specializations h of g such that
      1. h is consistent with d, and
      2. some member of S is more specific than h
    • Remove from G any hypothesis that is less general than another hypothesis in G