Probably Approximately Correct (PAC) learning - Python Automation and Machine Learning for ICs - - An Online Book - |
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Python Automation and Machine Learning for ICs http://www.globalsino.com/ICs/ | ||||||||
Chapter/Index: Introduction | A | B | C | D | E | F | G | H | I | J | K | L | M | N | O | P | Q | R | S | T | U | V | W | X | Y | Z | Appendix | ||||||||
================================================================================= Probably Approximately Correct (PAC) learning is a fundamental concept in learning theory. It deals with the probability of a learning algorithm producing a hypothesis that is approximately correct with high confidence. The equation below is related to the probably approximately correct (PAC) learning framework and specifically to the generalization error analysis: where,
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