Accord.NET Framework

SupportVectorMachine Methods |

The SupportVectorMachine type exposes the following members.

Methods

Name | Description | |
---|---|---|

Clone |
Creates a new object that is a copy of the current instance.
(Overrides SupportVectorMachineTKernelClone.) | |

Compress |
If this machine has a linear kernel, compresses all
support vectors into a single parameter vector.
(Inherited from SupportVectorMachineTKernel, TInput.) | |

Compute(TInput) | Obsolete.
Computes the given input to produce the corresponding output.
(Inherited from SupportVectorMachineTKernel, TInput.) | |

Compute(TInput, Double) | Obsolete.
Computes the given input to produce the corresponding output.
(Inherited from SupportVectorMachineTKernel, TInput.) | |

Decide(TInput) |
Computes class-label decisions for a given set of input vectors.
(Inherited from ClassifierBaseTInput, TClasses.) | |

Decide(TInput) |
Computes a class-label decision for a given input.
(Inherited from SupportVectorMachineTKernel, TInput.) | |

Decide(TInput, Boolean) |
Computes class-label decisions for the given input.
(Inherited from BinaryClassifierBaseTInput.) | |

Decide(TInput, TClasses) |
Computes a class-label decision for a given input.
(Inherited from ClassifierBaseTInput, TClasses.) | |

Equals | Determines whether the specified object is equal to the current object. (Inherited from Object.) | |

Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.) | |

FromLogisticRegression |
Performs an explicit conversion from LogisticRegression to SupportVectorMachine.
| |

FromRegression |
Performs an explicit conversion from MultipleLinearRegression to SupportVectorMachine.
| |

FromWeights |
Creates a new linear SupportVectorMachine
with the given set of linear weights.
| |

GetHashCode | Serves as the default hash function. (Inherited from Object.) | |

GetType | Gets the Type of the current instance. (Inherited from Object.) | |

LogLikelihood(TInput) |
Predicts a class label vector for the given input vector, returning the
log-likelihood that the input vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

LogLikelihood(TInput) |
Predicts a class label vector for the given input vector, returning the
log-likelihood that the input vector belongs to its predicted class.
(Inherited from SupportVectorMachineTKernel, TInput.) | |

LogLikelihood(TInput, Boolean) |
Predicts a class label for each input vector, returning the
log-likelihood that each vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

LogLikelihood(TInput, Double) |
Predicts a class label vector for the given input vector, returning the
log-likelihood that the input vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

LogLikelihood(TInput, Boolean) | ||

LogLikelihood(TInput, Boolean, Double) |
Predicts a class label for each input vector, returning the
log-likelihood that each vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

LogLikelihoods(TInput, Boolean) |
Predicts a class label vector for the given input vector, returning the
log-likelihoods of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

LogLikelihoods(TInput, Boolean) |
Predicts a class label vector for each input vector, returning the
log-likelihoods of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

LogLikelihoods(TInput, Boolean, Double) |
Predicts a class label vector for the given input vector, returning the
log-likelihoods of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

LogLikelihoods(TInput, Boolean, Double) |
Predicts a class label vector for each input vector, returning the
log-likelihoods of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) | |

Probabilities(TInput, Boolean) |
Predicts a class label vector for the given input vector, returning the
probabilities of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Probabilities(TInput, Boolean) |
Predicts a class label vector for each input vector, returning the
probabilities of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Probabilities(TInput, Boolean, Double) |
Predicts a class label vector for the given input vector, returning the
probabilities of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Probabilities(TInput, Boolean, Double) |
Predicts a class label vector for each input vector, returning the
probabilities of the input vector belonging to each possible class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Probability(TInput) |
Predicts a class label for the given input vector, returning the
probability that the input vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Probability(TInput) |
Predicts a class label for the given input vector, returning the
probability that the input vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Probability(TInput, Boolean) |
Predicts a class label for the given input vector, returning the
probability that the input vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Probability(TInput, Boolean) |
Predicts a class label for each input vector, returning the
probability that each vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Probability(TInput, Double) | ||

Probability(TInput, Boolean, Double) |
Predicts a class label for each input vector, returning the
probability that each vector belongs to its predicted class.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Score(TInput) |
Computes a numerical score measuring the association between
the given input vector and its most strongly
associated class (as predicted by the classifier).
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Score(TInput) |
Computes a numerical score measuring the association between
the given input vector and its most strongly
associated class (as predicted by the classifier).
(Inherited from SupportVectorMachineTKernel, TInput.) | |

Score(TInput, Boolean) |
Predicts a class label for the input vector, returning a
numerical score measuring the strength of association of the
input vector to its most strongly related class.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Score(TInput, Boolean) |
Predicts a class label for each input vector, returning a
numerical score measuring the strength of association of the
input vector to the most strongly related class.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Score(TInput, Double) |
Computes a numerical score measuring the association between
the given input vector and each class.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Score(TInput, Boolean, Double) |
Predicts a class label for each input vector, returning a
numerical score measuring the strength of association of the
input vector to the most strongly related class.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Scores(TInput) |
Computes a numerical score measuring the association between
the given input vector and each class.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Scores(TInput) |
Computes a numerical score measuring the association between
the given input vector and each class.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Scores(TInput, Boolean) |
Predicts a class label vector for the given input vector, returning a
numerical score measuring the strength of association of the input vector
to each of the possible classes.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Scores(TInput, Double) |
Computes a numerical score measuring the association between
the given input vector and each class.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Scores(TInput, Boolean) |
Predicts a class label vector for each input vector, returning a
numerical score measuring the strength of association of the input vector
to each of the possible classes.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Scores(TInput, Double) |
Computes a numerical score measuring the association between
the given input vector and each class.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Scores(TInput, Boolean, Double) |
Predicts a class label vector for the given input vector, returning a
numerical score measuring the strength of association of the input vector
to each of the possible classes.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

Scores(TInput, Boolean, Double) |
Predicts a class label vector for each input vector, returning a
numerical score measuring the strength of association of the input vector
to each of the possible classes.
(Inherited from BinaryScoreClassifierBaseTInput.) | |

ToMulticlass |
Views this instance as a multi-class generative classifier,
giving access to more advanced methods, such as the prediction
of integer labels.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

ToMultilabel |
Views this instance as a multi-label generative classifier,
giving access to more advanced methods, such as the prediction
of one-hot vectors.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

ToString | Returns a string that represents the current object. (Inherited from Object.) | |

ToWeights |
Converts a Linear-kernel machine into an array of
linear coefficients. The first position in the array is the
Threshold value. If this
machine is not linear, an exception will be thrown.
(Inherited from SupportVectorMachineTKernel.) | |

Transform(TInput) |
Applies the transformation to an input, producing an associated output.
(Inherited from ClassifierBaseTInput, TClasses.) | |

Transform(TInput) |
Applies the transformation to a set of input vectors,
producing an associated set of output vectors.
(Inherited from TransformBaseTInput, TOutput.) | |

Transform(TInput, Boolean) |
Applies the transformation to an input, producing an associated output.
(Inherited from BinaryClassifierBaseTInput.) | |

Transform(TInput, Int32) |
Applies the transformation to an input, producing an associated output.
(Inherited from BinaryClassifierBaseTInput.) | |

Transform(TInput, Boolean) |
Applies the transformation to an input, producing an associated output.
(Inherited from BinaryClassifierBaseTInput.) | |

Transform(TInput, Int32) |
Applies the transformation to an input, producing an associated output.
(Inherited from BinaryClassifierBaseTInput.) | |

Transform(TInput, Int32) |
Applies the transformation to an input, producing an associated output.
(Inherited from BinaryClassifierBaseTInput.) | |

Transform(TInput, Double) |
Applies the transformation to a set of input vectors,
producing an associated set of output vectors.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Transform(TInput, Double) |
Applies the transformation to a set of input vectors,
producing an associated set of output vectors.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Transform(TInput, Double) |
Applies the transformation to a set of input vectors,
producing an associated set of output vectors.
(Inherited from BinaryLikelihoodClassifierBaseTInput.) | |

Transform(TInput, TClasses) |
Applies the transformation to an input, producing an associated output.
(Inherited from ClassifierBaseTInput, TClasses.) |

Extension Methods

Name | Description | |
---|---|---|

HasMethod |
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.) | |

ToT | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) | |

ToT | Overloaded.
Converts an object into another type, irrespective of whether
the conversion can be done at compile time or not. This can be
used to convert generic types to numeric types during runtime.
(Defined by Matrix.) |

See Also