Machine Learning

UNIT-1 (A) Introduction   Introduction: Well-Posed Learning Problems Designing a Learning System Perspectives and Issues in Machine Learning Introduction to Supervised Unsupervised and Reinforcement Learning  

UNIT-1  Introduction & Concept Learning and the General to Specific Ordering   Introduction: Well-Posed Learning Problems Designing a Learning System Perspectives and Issues in Machine Learning Introduction to Supervised Unsupervised and Reinforcement Learning  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 

  1.      WELL-POSED LEARNING PROBLEMS Definition: A computer program is said to learn from experience E concerning some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E. To have a well-defined learning problem, three features need to be identified: 1. The class of tasks 2. The measure of performance to be improved 3. The source of experience   Examples 1. Checkers game: A computer program that learns to play checkers might improve its performance as measured by its ability to win at the class of tasks involving playing checkers games, through experience obtained by playing games against itself. Fig: Checker game board A checkers learning problem: •         Task T: playing checkers •         Performance measure P: percent of games won against opponents •         Training experience E: playing practice games against itself 2. A handwriting recognition learning problem: •