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gptkbp:instanceOf
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gptkb:statistical_analysis
|
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gptkbp:application
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gptkb:Gene_prediction
Machine translation
Handwriting recognition
Financial modeling
Part-of-speech tagging
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gptkbp:assumes
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gptkb:Markov_property
Observations are probabilistic functions of states
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gptkbp:canBe
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Continuous
Discrete
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gptkbp:canBeTrainedBy
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Expectation-maximization
|
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gptkbp:decodingAlgorithm
|
gptkb:Viterbi_algorithm
|
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gptkbp:generalizes
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gptkb:Markov_chain
|
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gptkbp:hasComponent
|
Transition probabilities
Emission probabilities
Hidden states
Initial state distribution
Observable states
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gptkbp:hasObservationSpace
|
Continuous
Finite
|
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gptkbp:hasStateSpace
|
Finite
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gptkbp:inferenceAlgorithm
|
Forward-backward algorithm
|
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gptkbp:input
|
Sequence of states
|
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gptkbp:limitation
|
Assumes independence of observations given state
Limited to first-order Markov property
|
|
gptkbp:mathematicalFoundation
|
gptkb:Probability_theory
gptkb:Linear_algebra
Statistics
|
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gptkbp:output
|
Sequence of observations
|
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gptkbp:parameter
|
gptkb:Baum-Welch_algorithm
|
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gptkbp:proposedBy
|
gptkb:Leonard_E._Baum
1966
|
|
gptkbp:relatedTo
|
gptkb:Dynamic_Bayesian_network
gptkb:Baum-Welch_algorithm
gptkb:Markov_chain
gptkb:Viterbi_algorithm
Forward-backward algorithm
|
|
gptkbp:type
|
Generative model
|
|
gptkbp:usedFor
|
Sequence modeling
Stochastic modeling
Temporal pattern recognition
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gptkbp:usedIn
|
gptkb:Bioinformatics
Natural language processing
Time series analysis
Speech recognition
Pattern recognition
|
|
gptkbp:visualizes
|
State diagram
|
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gptkbp:bfsParent
|
gptkb:Speech_Recognition
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gptkbp:bfsLayer
|
6
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|
https://www.w3.org/2000/01/rdf-schema#label
|
Hidden Markov Models
|