- Well-Posed Learning Problems
- Designing a Learning System
- Perspectives and Issues in Machine Learning
- Introduction to Supervised
- Unsupervised and Reinforcement Learning
Machine Learning 2 UNIT-1 (A) PPTs: Introduction PPTs
Machine Learning 2- UNIT-1 (A) Notes : Introduction & Concept Learning and the General to Specific Ordering Notes
- Well-Posed Learning Problems
- Designing a Learning System
- Perspectives and Issues in Machine Learning
- Introduction to Supervised
- Unsupervised and Reinforcement Learning
- 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
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:
•
Task T:
recognizing and classifying handwritten words within images
•
Performance measure P:
percent of words correctly classified
•
Training experience E:
a database of handwritten words with given classifications
3. A robot driving
learning problem:
•
Task T:
driving on public four-lane highways using vision sensors
•
Performance measure P:
average distance travelled before an error (as judged by human overseer)
•
Training experience E:
a sequence of images and steering commands recorded while observing a human
driver
About Machine Learning
Welcome! Your Hub for AI, Machine Learning, and Emerging Technologies In today’s rapidly evolving tech landscape, staying updated with the ...
-
This blog provides information for the following subjects 👉 Artificial Intelligence 👉 Machine Learning 👉 Machine Learning Programs 👉 ...
-
Machine Learning 👉 About Machine Learning 1 The Machine Learning Landscape Classification Support Vector Machines Decision Trees Ensem...
-
UNIT 3 Support Vector Machines MCQs -------------------------------------------------------------------------------------------------------...