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- __builtin__.object
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- DataSet
- Model
class DataSet(__builtin__.object) |
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A DataSet stores training data (examples of features and
desired corresponding output values). DataSets can be used
to train models (in order to do predictions.)
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Methods defined here:
- add(...)
- add({feature1:value1,feature2:value2},output)
Adds a row of training data to the model.
- save(...)
- save(filename)
Save training data to a file.
- train(...)
- train()
Train a classifier
Data and other attributes defined here:
- __new__ = <built-in method __new__ of type object at 0xb73f5880>
- T.__new__(S, ...) -> a new object with type S, a subtype of T
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class Model(__builtin__.object) |
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A Model can be used to predict values from (so far unknown)
input data. Models are "lightweight", in that they don't
store any data other than that needed to do predictions (in
particular, they don't contain any explicit training data)
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Methods defined here:
- generate_code(...)
- generate_code(language)
Generate code for this model
- predict(...)
- predict({feature1:value1,feature2:value2})
Evaluate the model for the given input. I.e. tries to estimate the target value (do a prediction).
- save(...)
- save(filename)
Save the model to a file
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