Course on Artificial Intelligence and Intelligent Systems Logical-Statistical models and parameter learning in the PRISM system
نویسنده
چکیده
3 More on using PRISM illustrated by a Bayesian Network 4 3.1 Defining a Bayesian network in PRISM . . . . . . . . . . . . . . . . . . . . . . . . . 5 3.2 Estimating probabilities for hidden random variables . . . . . . . . . . . . . . . . . . 6 3.3 Learning probabilities . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 3.4 A final remark on learning . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
منابع مشابه
Course on Artificial Intelligence and Intelligent Systems Hidden Markov Models and their implementation in the PRISM system
Contents 1 Introduction 2 2 A simple example 2 3 Providing more concise information 4 4 Using the HMM to produce abstract explanations of observations 5 5 A generic program structure for HMMs searching for the final state 6 6 Using learning to train HMMs (sketch) 8 7 Exercise: Spellchecking without a dictionary 9 7.
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