KernelDiscriminantAnalysis Properties |
The KernelDiscriminantAnalysis type exposes the following members.
Name | Description | |
---|---|---|
ClassCount |
Gets the observation count for each class.
(Inherited from BaseDiscriminantAnalysis.) | |
Classes |
Gets information about the distinct classes in the analyzed data.
(Inherited from BaseDiscriminantAnalysis.) | |
Classifications | Obsolete.
Gets the original classifications (labels) of the source data
given on the moment of creation of this analysis object.
(Inherited from BaseDiscriminantAnalysis.) | |
Classifier |
Gets a classification pipeline that can be used to classify
new samples into one of the NumberOfClasses
learned in this discriminant analysis. This pipeline is
only available after a call to the Learn(Double, Int32, Double) method.
| |
ClassMeans |
Gets the Mean vector for each class.
(Inherited from BaseDiscriminantAnalysis.) | |
ClassScatter |
Gets the Scatter matrix for each class.
(Inherited from BaseDiscriminantAnalysis.) | |
ClassStandardDeviations |
Gets the Standard Deviation vector for each class.
(Inherited from BaseDiscriminantAnalysis.) | |
CumulativeProportions |
The cumulative distribution of the discriminants factors proportions.
Also known as the cumulative energy of the first dimensions of the discriminant
space or as the amount of variance explained by those dimensions.
(Inherited from BaseDiscriminantAnalysis.) | |
DiscriminantMatrix | Obsolete.
Gets the Eigenvectors obtained during the analysis,
composing a basis for the discriminant factor space.
(Inherited from BaseDiscriminantAnalysis.) | |
DiscriminantProportions |
Gets the level of importance each discriminant factor has in
discriminant space. Also known as amount of variance explained.
(Inherited from BaseDiscriminantAnalysis.) | |
Discriminants |
Gets the discriminant factors in a object-oriented fashion.
(Inherited from BaseDiscriminantAnalysis.) | |
DiscriminantVectors |
Gets the Eigenvectors obtained during the analysis,
composing a basis for the discriminant factor space.
(Inherited from BaseDiscriminantAnalysis.) | |
Eigenvalues |
Gets the Eigenvalues found by the analysis associated
with each vector of the ComponentMatrix matrix.
(Inherited from BaseDiscriminantAnalysis.) | |
Input |
Gets or sets the matrix of original values used to create
this analysis. Those values are required to build kernel
(Gram) matrices when classifying new samples.
| |
Kernel |
Gets or sets the Kernel used in the analysis.
| |
Means |
Gets the mean of the original data given at method construction.
(Inherited from BaseDiscriminantAnalysis.) | |
NumberOfClasses |
Gets the number of classes in the analysis.
(Inherited from BaseDiscriminantAnalysis.) | |
NumberOfInputs |
Gets the number of inputs accepted by the model.
(Inherited from TransformBaseTInput, TOutput.) | |
NumberOfOutputs |
Gets the number of outputs generated by the model.
(Inherited from TransformBaseTInput, TOutput.) | |
NumberOfSamples |
Gets the number of samples used to create the analysis.
(Inherited from BaseDiscriminantAnalysis.) | |
ProjectionMeans |
Gets the feature space mean of the projected data.
(Inherited from BaseDiscriminantAnalysis.) | |
Regularization |
Gets or sets the regularization parameter to
avoid non-singularities at the solution.
| |
Result | Obsolete.
Gets the resulting projection of the source data given on
the creation of the analysis into discriminant space.
(Inherited from BaseDiscriminantAnalysis.) | |
ScatterBetweenClass |
Gets the Between-Class Scatter Matrix for the data.
(Inherited from BaseDiscriminantAnalysis.) | |
ScatterMatrix |
Gets the Total Scatter Matrix for the data.
(Inherited from BaseDiscriminantAnalysis.) | |
ScatterWithinClass |
Gets the Within-Class Scatter Matrix for the data.
(Inherited from BaseDiscriminantAnalysis.) | |
Source | Obsolete.
Returns the original supplied data to be analyzed.
(Inherited from BaseDiscriminantAnalysis.) | |
StandardDeviations |
Gets the standard mean of the original data given at method construction.
(Inherited from BaseDiscriminantAnalysis.) | |
Threshold |
Gets or sets the minimum variance proportion needed to keep a
discriminant component. If set to zero, all components will be
kept. Default is 0.001 (all components which contribute less
than 0.001 to the variance in the data will be discarded).
(Inherited from BaseDiscriminantAnalysis.) | |
Token |
Gets or sets a cancellation token that can be used to
stop the learning algorithm while it is running.
(Inherited from BaseDiscriminantAnalysis.) |