# Differences

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 courses:rg:2013:convolution-kernels [2013/03/11 18:54]dusek courses:rg:2013:convolution-kernels [2013/03/12 11:27]popel x was not rendered Both sides previous revision Previous revision 2013/03/12 11:27 popel x was not rendered2013/03/11 18:54 dusek 2013/03/11 18:49 dusek 2013/03/11 18:42 dusek 2013/03/11 18:42 dusek 2013/03/11 18:31 dusek 2013/02/26 10:03 dusek vytvořeno 2013/03/12 11:27 popel x was not rendered2013/03/11 18:54 dusek 2013/03/11 18:49 dusek 2013/03/11 18:42 dusek 2013/03/11 18:42 dusek 2013/03/11 18:31 dusek 2013/02/26 10:03 dusek vytvořeno Line 19: Line 19: * They are able to "generate" fake inputs, but this feat is not used very often. * They are able to "generate" fake inputs, but this feat is not used very often. * Examples: Naive Bayes, Mixtures of Gaussians, HMM, Bayesian Networks, Markov Random Fields * Examples: Naive Bayes, Mixtures of Gaussians, HMM, Bayesian Networks, Markov Random Fields - * **Discriminative models** do everything in one-step -- they learn the posterior P(y|x) as a function of some features of x. + * **Discriminative models** do everything in one-step -- they learn the posterior P(y|x) as a function of some features of x. * They are simpler and can use many more features, but are prone to missing inputs. * They are simpler and can use many more features, but are prone to missing inputs. - * Examples: SVM, Logistic Regression, Neuron. sítě, k-NN, Conditional Random Fields + * Examples: SVM, Logistic Regression, Neural network, k-NN, Conditional Random Fields - Each CFG rule generates just one level of the derivation tree. Therefore, using "standard" nonterminals, it is not possible to generate e.g. this sentence: - Each CFG rule generates just one level of the derivation tree. Therefore, using "standard" nonterminals, it is not possible to generate e.g. this sentence: * ''(S (NP (PRP He)) (VP (VBD saw)(NP (PRP himself))))'' * ''(S (NP (PRP He)) (VP (VBD saw)(NP (PRP himself))))''

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