datatable.models.LinearModel¶
This class implements the Linear model with the
stochastic gradient descent learning. It supports linear
regression, as well as binomial and multinomial classification.
Both .fit()
and .predict()
methods are fully parallel.
Construction¶
Construct a |
Methods¶
Train model on the input samples and targets. |
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Report model status. |
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Predict for the input samples. |
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Reset the model. |
Properties¶
Initial learning rate. |
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Decay for the |
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Drop rate for the |
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Learning rate schedule. |
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An option to control precision of the internal computations. |
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Classification labels. |
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L1 regularization parameter. |
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L2 regularization parameter. |
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Model coefficients. |
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Model type to be built. |
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An option to indicate if the “negative” class should be a created for multinomial classification. |
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Number of training epochs. |
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All the input model parameters as a named tuple. |
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Seed for the quasi-random data shuffling. |