Title: Instructor : Saeed Shiry
1??????? ?????
- Instructor Saeed Shiry
- Mitchell Ch. 1
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- ????? ????? ???? ?? ???????
- ??????? ????? ??? ?????? ????? ???? ? ?? ??? ??
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?????? ??? ?? ???? ???. ??????? ???? ??? ????
????? ?? ?????? ?????? ? ?? ???? ?? ???.
3????? ??????? ?????
- From Mitchell (1997)
- A computer program is said to learn from
experimence E with respect to some class of tasks
T and performance measure P, if its performance
at tasks in T, as measured by P, improves with
experience E. - From Witten and Frank (2000)
- things learn when they change their behavior in a
way that makes them perform better in the future. - From Ethem Alpaydin (2010)
- Machine learning is programming computers to
optimize a performance criterion using example
data or past experience. - In practice this means
- We have sets of examples from which we want to
extract regularities.
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??????? ????? ? ?????????????PAC . ?? ??? ?????
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6?????
- ???? ???
- Machine learning by Tom Mitchell, McGraw Hill,
1997. - Pattern Recognition and Machine Learning,
Christopher M. Bishop, 2006. - Introduction to Machine Learning, Second Edition.
Ethem Alpaydin,The MIT Press, 2010. - ???? ?????
- Reinforcement learning An introduction, By
Richard S. Sutton Andrew G Barto. - ???? ??? ??? ?? ???? ???? ??? ???? ?????? ????
???.
7???? ???
- http//ceit.aut.ac.ir/shiry/lecture/machine-learn
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- ???? ?? ??? ?????? ??? ????? ??? ?? ????? ???
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12?????? ???
????? Introduction
??????? ????? Concept learning
???? ????? ???? Decision Tree Learning
???? ??? ???? ?????? Artificial Neural Networks
??????? ????? Evaluating Hypothesis
??????? ????? ? ???? ??? ???? ???? Bayesian learning
????? ??????? ???????? Computational Learning Theory
??????? ????? Instance based learning
???????? ????? Genetic Algorithms
??????? ?????? Reinforcement Learning
????? ????? ??????? Support Vector Machine
??? ???? ????? Hidden Markov Model
???????? ?????? ????? Cellular Learning Automata
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?? ???? ???? ???? ???????. - Numeric prediction
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560 1012 893 2196 936 37 79 76 130 82
27????? ?? ??????? ?? ????
- Input feature x(i) ????? ????
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- lt x(i), y(i) gt ???? ???????
- x(i), y(i) , i1m ?????? ???????
- ??? ???????
- ?? ????? ?? ?????? ??????? ???????? ????? ?????
h x? y ??? ?????? ?? h(x) ?????? ????? y
?? ????? ??? ????. ??? ???? ????? ? ??
hypothesis ?????? ?????.
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?????? ???? ????? ????. - Function Approximation
- ?? ???????? ?? ??? ???? ???? ???? ??? ???? ??
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???? ?????. - ???? ???? ??? x10,x21,x32,x40,x50,x60 ??
???? ??? ???? ? x11,x20,x30,x40,x50,x60 ??
???? ???? ???? ?? ?????? ????
V(x10,x21,x32,x40,x50,x60)100
- V(x10,x21,x32,x40,x50,x60) -100
- ?? ?????? ???? ??????? ????? ?? ?? ????????
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57Learning Requires Bias
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????.
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