Machine Learning

UNIT-1 (B)   Concept Learning and the General to Specific Ordering   Concept Learning and the General to Specific Ordering   Introduction A Concept Learning Task Concept Learning as Search Find-S: Finding a Maximally Specific Hypothesis Version Spaces and the Candidate Elimination Algorithm  

  CONCEPT LEARNING AS SEARCH ·        Concept learning can be viewed as ·        the task of searching through a large space of hypotheses implicitly defined by the hypothesis representation. ·        The goal of this search is to ·        find the hypothesis that best fits the training examples . Example: •         Consider the instances X and hypotheses H in the EnjoySport learning task. •         The attribute •         Sky has three possible values , and •         AirTemp , Humidity , Wind, Water, Forecast each have two possible values , •         the instance space X contains •         exactly 3*2*2*2*2*2 = 96 distinct instances •         5*4*4*4*4*4 = 5120 syntactically distinct hypotheses within H . •         Every hypothesis containing one or more "Φ" symbols represents the empty set of instances ; that is, it classifies every instance as negative . •         1 + (4*3*3*3*3*3) = 973 Semantically distinct hypotheses . A CONCEPT LEAR