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KMedoidsClusterCollectionT Class |
k-Medoids cluster collection.
Inheritance HierarchySystemObject
Accord.MachineLearningTransformBaseT, Int32
Accord.MachineLearningClassifierBaseT, Int32
Accord.MachineLearningMulticlassClassifierBaseT
Accord.MachineLearningMulticlassScoreClassifierBaseT
Accord.MachineLearningKMedoidsClusterCollectionT
Accord.MachineLearningTransformBaseT, Int32
Accord.MachineLearningClassifierBaseT, Int32
Accord.MachineLearningMulticlassClassifierBaseT
Accord.MachineLearningMulticlassScoreClassifierBaseT
Accord.MachineLearningKMedoidsClusterCollectionT
Namespace: Accord.MachineLearning
Assembly: Accord.MachineLearning (in Accord.MachineLearning.dll) Version: 3.8.0
Syntax[SerializableAttribute] public class KMedoidsClusterCollection<T> : MulticlassScoreClassifierBase<T[]>, ICentroidClusterCollection<T[], KMedoidsClusterCollectionTKMedoidsCluster>, ICentroidClusterCollection<T[], T[], KMedoidsClusterCollectionTKMedoidsCluster>, IClusterCollectionEx<T[], KMedoidsClusterCollectionTKMedoidsCluster>, IEnumerable
Type Parameters
- T
The KMedoidsClusterCollectionT type exposes the following members.
Constructors| Name | Description | |
|---|---|---|
 | KMedoidsClusterCollectionT |
Initializes a new instance of the KMedoidsClusterCollectionT class.
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Properties| Name | Description | |
|---|---|---|
 | Centroids |
Gets or sets the clusters' centroids.
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| Clusters |
Gets the collection of clusters currently modeled by the clustering algorithm.
|
| Count |
Gets the number of clusters in the collection.
|
| Distance |
Gets or sets the distance function used to measure the distance
between a point and the cluster centroid in this clustering definition.
|
| Item |
Gets the KMedoidsClusterCollectionTKMedoidsCluster at the specified index.
|
| NumberOfClasses |
Gets the number of classes expected and recognized by the classifier.
(Inherited from ClassifierBaseTInput, TClasses.) |
| 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.) |
| Proportions |
Gets the proportion of samples in each cluster.
|
Methods| Name | Description | |
|---|---|---|
| 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 MulticlassScoreClassifierBaseTInput.) |
| Decide(TInput, TClasses) |
Computes a class-label decision for a given input.
(Inherited from ClassifierBaseTInput, TClasses.) |
| Decide(TInput, Boolean) |
Computes class-label decisions for the given input.
(Inherited from MulticlassClassifierBaseTInput.) |
| Decide(TInput, Double) |
Computes class-label decisions for the given input.
(Inherited from MulticlassClassifierBaseTInput.) |
| Decide(TInput, Int32) |
Computes class-label decisions for the given input.
(Inherited from MulticlassClassifierBaseTInput.) |
| Decide(TInput, Double) |
Computes a class-label decision for a given input.
(Inherited from MulticlassClassifierBaseTInput.) |
| Distortion |
Calculates the average square distance from the data points
to the nearest clusters' centroids.
|
| 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.) |
| GetEnumerator |
Returns an enumerator that iterates through the collection.
|
| GetHashCode | Serves as the default hash function. (Inherited from Object.) |
| GetType | Gets the Type of the current instance. (Inherited from Object.) |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object.) |
| Randomize |
Randomizes the clusters inside a dataset.
|
| 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 MulticlassScoreClassifierBaseTInput.) |
| 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 MulticlassScoreClassifierBaseTInput.) |
| Score(T, Int32) |
Computes a numerical score measuring the association between
the given input vector and a given
classIndex.
(Overrides MulticlassScoreClassifierBaseTInputScore(TInput, Int32).) |
| Score(TInput, Int32) |
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 MulticlassScoreClassifierBaseTInput.) |
| Score(TInput, Double) |
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 MulticlassScoreClassifierBaseTInput.) |
| Score(TInput, Int32) |
Computes a numerical score measuring the association between
the given input vector and a given
classIndex.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| Score(TInput, Int32) |
Computes a numerical score measuring the association between
the given input vector and a given
classIndex.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| Score(TInput, Int32) |
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 MulticlassScoreClassifierBaseTInput.) |
| Score(TInput, Int32, Double) |
Computes a numerical score measuring the association between
the given input vector and a given
classIndex.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| Score(TInput, Int32, Double) |
Computes a numerical score measuring the association between
the given input vector and a given
classIndex.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| Score(TInput, Int32, 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 MulticlassScoreClassifierBaseTInput.) |
| Scores(TInput) |
Computes a numerical score measuring the association between
the given input vector and each class.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| Scores(TInput) |
Computes a numerical score measuring the association between
the given input vector and each class.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| Scores(TInput, Double) |
Computes a numerical score measuring the association between
the given input vector and each class.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| Scores(TInput, Int32) |
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 MulticlassScoreClassifierBaseTInput.) |
| Scores(TInput, Double) |
Computes a numerical score measuring the association between
the given input vector and each class.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| Scores(TInput, Int32) |
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 MulticlassScoreClassifierBaseTInput.) |
| Scores(TInput, Int32, 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 MulticlassScoreClassifierBaseTInput.) |
| Scores(TInput, Int32, 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 MulticlassScoreClassifierBaseTInput.) |
| ToMulticlass |
Views this instance as a multi-class generative classifier.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| ToMultilabel |
Views this instance as a multi-label distance classifier,
giving access to more advanced methods, such as the prediction
of one-hot vectors.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| 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, TClasses) |
Applies the transformation to an input, producing an associated output.
(Inherited from ClassifierBaseTInput, TClasses.) |
| Transform(TInput, Boolean) |
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassClassifierBaseTInput.) |
| Transform(TInput, Int32) |
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassClassifierBaseTInput.) |
| Transform(TInput, Boolean) |
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassClassifierBaseTInput.) |
| Transform(TInput, Double) |
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassClassifierBaseTInput.) |
| Transform(TInput, Int32) |
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassClassifierBaseTInput.) |
| Transform(TInput, Double) |
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| Transform(TInput, Double) |
Applies the transformation to an input, producing an associated output.
(Inherited from MulticlassScoreClassifierBaseTInput.) |
| Transform(T, Double, Double) |
Transform data points into feature vectors containing the
distance between each point and each of the clusters.
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| Transform(T, Int32, Double, Double) |
Transform data points into feature vectors containing the
distance between each point and each of the clusters.
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Extension Methods| Name | Description | |
|---|---|---|
 | HasMethod |
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.) |
| IsEqual |
Compares two objects for equality, performing an elementwise
comparison if the elements are vectors or matrices.
(Defined by Matrix.) |
| SetEqualsKMedoidsClusterCollectionTKMedoidsCluster |
Compares two enumerables for set equality. Two
enumerables are set equal if they contain the
same elements, but not necessarily in the same
order.
(Defined by Matrix.) |
| To(Type) | 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 ExtensionMethods.) |
See Also