# Changes between Version 7 and Version 8 of tutorial/ProbabilisticLearningModels

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Timestamp:
08/17/09 08:49:31 (13 years ago)
Comment:

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 v7 1. Train your model with your training data 1. Classify your test data. 1. Evaluate results === Relational Classification === Relational data consists of entities, described by features and statisitcal dependencies between entities. ==== Nearest Neighbor (1-NN or NN) ==== ==== Conditional Random Field ==== A conditional random field is a conditional distribution {{{ #!latex $P(A|B)$ }}} with an associated graphical structure. ==== Bayes Rule ==== {{{ #!latex $P(A|B) = \frac{P(B|A) \cdot P(A)}{P(B)}$ #!latex $P(A|B) = \frac{P(B|A) \cdot P(A)}{P(B)}$ }}}