Accord.NET Framework

GeneralizedLinearRegression Methods |

The GeneralizedLinearRegression type exposes the following members.

Methods

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

ChiSquare(Double, Double) |
The likelihood ratio test of the overall model, also called the model chi-square test.
| |

ChiSquare(Double, Double, Double) |
The likelihood ratio test of the overall model, also called the model chi-square test.
| |

Clone |
Creates a new GeneralizedLinearRegression that is a copy of the current instance.
| |

Compute(Double) | Obsolete.
Computes the model output for the given input vector.
| |

Compute(Double) | Obsolete.
Computes the model output for each of the given input vectors.
| |

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

Decide(Double) |
Computes a class-label decision for a given input.
(Overrides ClassifierBaseTInput, TClassesDecide(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 | Obsolete.
Creates a GeneralizedLinearRegression from a LogisticRegression object.
| |

GetCoefficient |
Gets a coefficient value, where 0 is the intercept term
and the other coefficients are indexed starting at 1.
| |

GetConfidenceInterval |
Gets the confidence interval for an input point.
| |

GetDegreesOfFreedom |
Gets the degrees of freedom when fitting the regression.
| |

GetDeviance(Double, Double) |
Gets the Deviance for the model.
| |

GetDeviance(Double, Double, Double) |
Gets the Deviance for the model.
| |

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

GetLogLikelihood(Double, Double) |
Gets the Log-Likelihood for the model.
| |

GetLogLikelihood(Double, Double, Double) |
Gets the Log-Likelihood for the model.
| |

GetLogLikelihoodRatio(Double, Double, GeneralizedLinearRegression) |
Gets the Log-Likelihood Ratio between two models.
| |

GetLogLikelihoodRatio(Double, Double, Double, GeneralizedLinearRegression) |
Gets the Log-Likelihood Ratio between two models.
| |

GetPredictionInterval |
Gets the prediction interval for an input point.
| |

GetPredictionStandardError |
Gets the standard error of the prediction for a particular input vector.
| |

GetStandardError |
Gets the standard error of the fit for a particular input vector.
| |

GetStandardErrors |
Gets the standard error for each coefficient.
| |

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

GetWaldTest |
Gets the Wald Test for a given coefficient.
| |

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(Double) |
Predicts a class label vector for the given input vector, returning the
log-likelihood that the input vector belongs to its predicted class.
(Overrides BinaryLikelihoodClassifierBaseTInputLogLikelihood(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(Double, 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(Double) |
Computes a numerical score measuring the association between
the given input vector and its most strongly
associated class (as predicted by the classifier).
(Overrides BinaryLikelihoodClassifierBaseTInputScore(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.) | |

SetCoefficient |
Sets a coefficient value, where 0 is the intercept term
and the other coefficients are indexed starting at 1.
| |

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.) | |

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