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Questions and Answers
What is the fundamental statistical approach to the problem of pattern classification?
What is the fundamental statistical approach to the problem of pattern classification?
- Frequentist Decision Theory
- Naive Bayes Classifier
- Maximum Likelihood Estimation
- Bayesian Decision Theory (correct)
In Bayesian decision theory, what is the simplest risk?
In Bayesian decision theory, what is the simplest risk?
- Likelihood function
- Classification error (correct)
- Expected cost
- Posterior probability
What does the term 'state of nature' refer to in Bayesian decision theory?
What does the term 'state of nature' refer to in Bayesian decision theory?
- Evidence probabilities
- Feature values
- Class label (correct)
- Prior probabilities
What does the probability density function p(x) represent in pattern classification?
What does the probability density function p(x) represent in pattern classification?
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What does the conditional probability density p(x/ωj) represent in Bayesian decision theory?
What does the conditional probability density p(x/ωj) represent in Bayesian decision theory?
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Study Notes
Pattern Classification and Bayesian Decision Theory
- The fundamental statistical approach to the problem of pattern classification is based on Bayesian decision theory.
Risk in Bayesian Decision Theory
- The simplest risk in Bayesian decision theory is the Bayes risk, which is the minimum expected risk achievable by a classifier.
State of Nature in Bayesian Decision Theory
- The term 'state of nature' in Bayesian decision theory refers to the underlying class or label of the pattern, represented by ω (omega).
Probability Density Functions in Pattern Classification
- The probability density function p(x) represents the probability distribution of the feature vector x in pattern classification.
- The conditional probability density p(x/ωj) represents the probability distribution of the feature vector x given the state of nature ωj (omega j), which is the probability of observing x given that the pattern belongs to class ωj.
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