Package | Description |
---|---|
org.tribuo.classification.explanations.lime |
Provides an implementation of LIME (Locally Interpretable Model Explanations).
|
org.tribuo.classification.sgd |
Provides infrastructure for Stochastic Gradient Descent for classification problems.
|
org.tribuo.classification.sgd.crf |
Provides an implementation of a linear chain CRF trained using Stochastic Gradient Descent.
|
org.tribuo.classification.sgd.objectives |
Provides classification loss functions for Stochastic Gradient Descent.
|
org.tribuo.clustering.kmeans |
Provides a multithreaded implementation of K-Means, with a
configurable distance function.
|
org.tribuo.common.tree |
Provides common functionality for building decision trees, irrespective
of the predicted
Output . |
org.tribuo.common.xgboost |
Provides abstract classes for interfacing with XGBoost abstracting away all the
Output
dependent parts. |
org.tribuo.interop |
This package contains the abstract implementation of an external model
trained by something outside of Tribuo.
|
org.tribuo.interop.onnx |
This package contains a Tribuo wrapper around the ONNX Runtime.
|
org.tribuo.interop.tensorflow |
Provides an interface to Tensorflow, allowing the training of non-sequential models using any supported
Tribuo output type.
|
org.tribuo.math |
Contains the implementation of Tribuo's math library, it's gradient descent optimisers, kernels and a set of
math related utils.
|
org.tribuo.math.kernel |
Provides a
Kernel interface for Mercer kernels, along with implementations of standard kernels. |
org.tribuo.math.la |
Provides a linear algebra system used for numerical operations in Tribuo.
|
org.tribuo.math.optimisers |
Provides implementations of
StochasticGradientOptimiser . |
org.tribuo.math.optimisers.util |
Provides some utility tensors for use in gradient optimisers.
|
org.tribuo.math.util |
Provides math related util classes.
|
org.tribuo.regression.impl | |
org.tribuo.regression.sgd |
Provides infrastructure for Stochastic Gradient Descent based regression models.
|
org.tribuo.regression.sgd.linear |
Provides an implementation of linear regression using Stochastic Gradient Descent.
|
org.tribuo.regression.sgd.objectives |
Provides regression loss functions for Stochastic Gradient Descent.
|
org.tribuo.regression.slm |
Provides implementations of sparse linear regression using various forms of regularisation penalty.
|
Class and Description |
---|
SparseVector
A sparse vector.
|
Class and Description |
---|
SGDVector
Interface for 1 dimensional
Tensor s. |
SparseVector
A sparse vector.
|
Class and Description |
---|
DenseMatrix
A dense matrix, backed by a primitive array.
|
DenseVector
A dense vector, backed by a double array.
|
SparseVector
A sparse vector.
|
Tensor
An interface for Tensors, currently Vectors and Matrices.
|
Class and Description |
---|
SGDVector
Interface for 1 dimensional
Tensor s. |
Class and Description |
---|
DenseVector
A dense vector, backed by a double array.
|
SparseVector
A sparse vector.
|
Class and Description |
---|
SparseVector
A sparse vector.
|
Class and Description |
---|
SparseVector
A sparse vector.
|
Class and Description |
---|
SparseVector
A sparse vector.
|
Class and Description |
---|
SparseVector
A sparse vector.
|
Class and Description |
---|
SparseVector
A sparse vector.
|
Class and Description |
---|
DenseMatrix
A dense matrix, backed by a primitive array.
|
SGDVector
Interface for 1 dimensional
Tensor s. |
SparseVector
A sparse vector.
|
Tensor
An interface for Tensors, currently Vectors and Matrices.
|
Class and Description |
---|
SparseVector
A sparse vector.
|
Class and Description |
---|
DenseMatrix
A dense matrix, backed by a primitive array.
|
DenseSparseMatrix
A matrix which is dense in the first dimension and sparse in the second.
|
DenseVector
A dense vector, backed by a double array.
|
Matrix
Interface for 2 dimensional
Tensor s. |
MatrixIterator |
MatrixTuple
A mutable tuple used to avoid allocation when iterating a matrix.
|
SGDVector
Interface for 1 dimensional
Tensor s. |
SparseVector
A sparse vector.
|
Tensor
An interface for Tensors, currently Vectors and Matrices.
|
VectorIterator |
VectorTuple
A mutable tuple used to avoid allocation when iterating a vector.
|
Class and Description |
---|
Tensor
An interface for Tensors, currently Vectors and Matrices.
|
Class and Description |
---|
DenseMatrix
A dense matrix, backed by a primitive array.
|
DenseVector
A dense vector, backed by a double array.
|
Matrix
Interface for 2 dimensional
Tensor s. |
MatrixIterator |
SGDVector
Interface for 1 dimensional
Tensor s. |
Tensor
An interface for Tensors, currently Vectors and Matrices.
|
VectorIterator |
Class and Description |
---|
DenseSparseMatrix
A matrix which is dense in the first dimension and sparse in the second.
|
SparseVector
A sparse vector.
|
Class and Description |
---|
SparseVector
A sparse vector.
|
Class and Description |
---|
DenseVector
A dense vector, backed by a double array.
|
SGDVector
Interface for 1 dimensional
Tensor s. |
Class and Description |
---|
DenseMatrix
A dense matrix, backed by a primitive array.
|
Class and Description |
---|
DenseVector
A dense vector, backed by a double array.
|
SGDVector
Interface for 1 dimensional
Tensor s. |
Class and Description |
---|
SparseVector
A sparse vector.
|
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