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Package Bio :: Module MaxEntropy |
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Maximum Entropy code.
Uses Improved Iterative Scaling: XXX ref
# XXX need to define terminologyClasses | |
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MaxEntropy |
Holds information for a Maximum Entropy classifier. |
Function Summary | |
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calculate(me, observation) -> list of log probs | |
classify(me, observation) -> class | |
train(training_set, results, feature_fns[, update_fn]) -> MaxEntropy object |
Function Details |
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calculate(me, observation)calculate(me, observation) -> list of log probs Calculate the log of the probability for each class. me is a MaxEntropy object that has been trained. observation is a vector representing the observed data. The return value is a list of unnormalized log probabilities for each class. |
classify(me, observation)classify(me, observation) -> class Classify an observation into a class. |
train(training_set, results, feature_fns, update_fn=None)train(training_set, results, feature_fns[, update_fn]) -> MaxEntropy object Train a maximum entropy classifier on a training set. training_set is a list of observations. results is a list of the class assignments for each observation. feature_fns is a list of the features. These are callback functions that take an observation and class and return a 1 or 0. update_fn is a callback function that's called at each training iteration. It is passed a MaxEntropy object that encapsulates the current state of the training. |
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