Class LinearParameters
java.lang.Object
org.tribuo.math.LinearParameters
- All Implemented Interfaces:
Serializable,FeedForwardParameters,Parameters
A
Parameters for producing linear models.- See Also:
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Constructor Summary
ConstructorsConstructorDescriptionLinearParameters(int numFeatures, int numLabels) Constructor.LinearParameters(DenseMatrix weightMatrix) Constructs a LinearParameters wrapped around a weight matrix. -
Method Summary
Modifier and TypeMethodDescriptioncopy()Returns a copy of the parameters.Tensor[]get()Get a reference to the underlyingTensorarray.Tensor[]This returns aDenseMatrixthe same size as the Parameters.Returns the weight matrix.Tensor[]Generate the gradients for a particular feature vector given the loss and the per output gradients.Tensor[]Merge together an array of gradient arrays.Generates an unnormalised prediction by leftMultiply'ing the weights with the incoming features.voidSet the underlyingTensorarray to newWeights.voidApply gradients to the parameters.
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Constructor Details
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LinearParameters
public LinearParameters(int numFeatures, int numLabels) Constructor. The number of features and the number of outputs must be fixed and known in advance.- Parameters:
numFeatures- The number of features in the training dataset (excluding the bias).numLabels- The number of outputs in the training dataset.
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LinearParameters
Constructs a LinearParameters wrapped around a weight matrix.Used for serialization compatibility with Tribuo 4.0.
- Parameters:
weightMatrix- The weight matrix to wrap.
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Method Details
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predict
Generates an unnormalised prediction by leftMultiply'ing the weights with the incoming features.- Specified by:
predictin interfaceFeedForwardParameters- Parameters:
example- A feature vector- Returns:
- A
DenseVectorcontaining a score for each label.
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gradients
public Tensor[] gradients(com.oracle.labs.mlrg.olcut.util.Pair<Double, SGDVector> score, SGDVector features) Generate the gradients for a particular feature vector given the loss and the per output gradients. This parameters returns a single elementTensorarray.- Specified by:
gradientsin interfaceFeedForwardParameters- Parameters:
score- The Pair returned by the objective.features- The feature vector.- Returns:
- A
Tensorarray with a singleMatrixcontaining all gradients.
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getEmptyCopy
This returns aDenseMatrixthe same size as the Parameters.- Specified by:
getEmptyCopyin interfaceParameters- Returns:
- A
Tensorarray containing a singleDenseMatrix.
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get
Description copied from interface:ParametersGet a reference to the underlyingTensorarray.- Specified by:
getin interfaceParameters- Returns:
- The parameters.
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getWeightMatrix
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set
Description copied from interface:ParametersSet the underlyingTensorarray to newWeights.- Specified by:
setin interfaceParameters- Parameters:
newWeights- New parameters to store in this object.
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update
Description copied from interface:ParametersApply gradients to the parameters. Assumes that gradients is the same length as the parameters, and eachTensoris the same size as the corresponding one from the parameters.The gradients are added to the parameters.
- Specified by:
updatein interfaceParameters- Parameters:
gradients- ATensorarray of updates, with the length equal toParameters.get().length.
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merge
Description copied from interface:ParametersMerge together an array of gradient arrays. Assumes the first dimension is the number of gradient arrays and the second dimension is the number of parameterTensors.- Specified by:
mergein interfaceParameters- Parameters:
gradients- An array of gradient update arrays.size- The number of elements of gradients to merge. Allows gradients to have unused elements.- Returns:
- A single
Tensorarray of the summed gradients.
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copy
Description copied from interface:FeedForwardParametersReturns a copy of the parameters.- Specified by:
copyin interfaceFeedForwardParameters- Returns:
- A copy of the model parameters.
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