MLPACK
1.0.4
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This class implements K-Means clustering. More...
Public Member Functions | |
KMeans (const size_t maxIterations=1000, const double overclusteringFactor=1.0, const DistanceMetric metric=DistanceMetric(), const InitialPartitionPolicy partitioner=InitialPartitionPolicy(), const EmptyClusterPolicy emptyClusterAction=EmptyClusterPolicy()) | |
Create a K-Means object and (optionally) set the parameters which K-Means will be run with. | |
template<typename MatType > | |
void | Cluster (const MatType &data, const size_t clusters, arma::Col< size_t > &assignments) const |
Perform K-Means clustering on the data, returning a list of cluster assignments. | |
const EmptyClusterPolicy & | EmptyClusterAction () const |
Get the empty cluster policy. | |
EmptyClusterPolicy & | EmptyClusterAction () |
Modify the empty cluster policy. | |
template<typename MatType > | |
void | FastCluster (MatType &data, const size_t clusters, arma::Col< size_t > &assignments) const |
size_t | MaxIterations () const |
Get the maximum number of iterations. | |
void | MaxIterations (const size_t maxIterations) |
Set the maximum number of iterations. | |
const DistanceMetric & | Metric () const |
Get the distance metric. | |
DistanceMetric & | Metric () |
Modify the distance metric. | |
double | OverclusteringFactor () const |
Return the overclustering factor. | |
void | OverclusteringFactor (const double overclusteringFactor) |
Set the overclustering factor. | |
const InitialPartitionPolicy & | Partitioner () const |
Get the initial partitioning policy. | |
InitialPartitionPolicy & | Partitioner () |
Modify the initial partitioning policy. | |
Private Attributes | |
EmptyClusterPolicy | emptyClusterAction |
Instantiated empty cluster policy. | |
size_t | maxIterations |
Maximum number of iterations before giving up. | |
DistanceMetric | metric |
Instantiated distance metric. | |
double | overclusteringFactor |
Factor controlling how many clusters are actually found. | |
InitialPartitionPolicy | partitioner |
Instantiated initial partitioning policy. |
This class implements K-Means clustering.
This implementation supports overclustering, which means that more clusters than are requested will be found; then, those clusters will be merged together to produce the desired number of clusters.
Two template parameters can (optionally) be supplied: the policy for how to find the initial partition of the data, and the actions to be taken when an empty cluster is encountered, as well as the distance metric to be used.
A simple example of how to run K-Means clustering is shown below.
extern arma::mat data; // Dataset we want to run K-Means on. arma::Col<size_t> assignments; // Cluster assignments. KMeans<> k(); // Default options. k.Cluster(data, 3, assignments); // 3 clusters. // Cluster using the Manhattan distance, 100 iterations maximum, and an // overclustering factor of 4.0. KMeans<metric::ManhattanDistance> k(100, 4.0); k.Cluster(data, 6, assignments); // 6 clusters.
DistanceMetric | The distance metric to use for this KMeans; see metric::LMetric for an example. |
InitialPartitionPolicy | Initial partitioning policy; must implement a default constructor and 'void Cluster(const arma::mat&, const size_t, arma::Col<size_t>&)'. |
EmptyClusterPolicy | Policy for what to do on an empty cluster; must implement a default constructor and 'void EmptyCluster(const arma::mat&, arma::Col<size_t&)'. |
Definition at line 73 of file kmeans.hpp.
mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::KMeans | ( | const size_t | maxIterations = 1000 , |
const double | overclusteringFactor = 1.0 , |
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const DistanceMetric | metric = DistanceMetric() , |
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const InitialPartitionPolicy | partitioner = InitialPartitionPolicy() , |
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const EmptyClusterPolicy | emptyClusterAction = EmptyClusterPolicy() |
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) |
Create a K-Means object and (optionally) set the parameters which K-Means will be run with.
This implementation allows a few strategies to improve the performance of K-Means, including "overclustering" and disallowing empty clusters.
The overclustering factor controls how many clusters are actually found; for instance, with an overclustering factor of 4, if K-Means is run to find 3 clusters, it will actually find 12, then merge the nearest clusters until only 3 are left.
maxIterations | Maximum number of iterations allowed before giving up (0 is valid, but the algorithm may never terminate). |
overclusteringFactor | Factor controlling how many extra clusters are found and then merged to get the desired number of clusters. |
metric | Optional DistanceMetric object; for when the metric has state it needs to store. |
partitioner | Optional InitialPartitionPolicy object; for when a specially initialized partitioning policy is required. |
emptyClusterAction | Optional EmptyClusterPolicy object; for when a specially initialized empty cluster policy is required. |
void mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::Cluster | ( | const MatType & | data, |
const size_t | clusters, | ||
arma::Col< size_t > & | assignments | ||
) | const |
Perform K-Means clustering on the data, returning a list of cluster assignments.
Optionally, the vector of assignments can be set to an initial guess of the cluster assignments; to do this, the number of elements in the list of assignments must be equal to the number of points (columns) in the dataset.
MatType | Type of matrix (arma::mat or arma::spmat). |
data | Dataset to cluster. |
clusters | Number of clusters to compute. |
assignments | Vector to store cluster assignments in. Can contain an initial guess at cluster assignments. |
const EmptyClusterPolicy& mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::EmptyClusterAction | ( | ) | const [inline] |
Get the empty cluster policy.
Definition at line 171 of file kmeans.hpp.
References mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::emptyClusterAction.
EmptyClusterPolicy& mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::EmptyClusterAction | ( | ) | [inline] |
Modify the empty cluster policy.
Definition at line 176 of file kmeans.hpp.
References mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::emptyClusterAction.
void mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::FastCluster | ( | MatType & | data, |
const size_t | clusters, | ||
arma::Col< size_t > & | assignments | ||
) | const |
size_t mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::MaxIterations | ( | ) | const [inline] |
Get the maximum number of iterations.
Definition at line 150 of file kmeans.hpp.
References mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::maxIterations.
void mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::MaxIterations | ( | const size_t | maxIterations | ) | [inline] |
Set the maximum number of iterations.
Definition at line 155 of file kmeans.hpp.
References mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::maxIterations.
const DistanceMetric& mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::Metric | ( | ) | const [inline] |
Get the distance metric.
Definition at line 161 of file kmeans.hpp.
References mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::metric.
DistanceMetric& mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::Metric | ( | ) | [inline] |
Modify the distance metric.
Definition at line 163 of file kmeans.hpp.
References mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::metric.
double mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::OverclusteringFactor | ( | ) | const [inline] |
Return the overclustering factor.
Definition at line 130 of file kmeans.hpp.
References mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::overclusteringFactor.
void mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::OverclusteringFactor | ( | const double | overclusteringFactor | ) | [inline] |
Set the overclustering factor.
Definition at line 135 of file kmeans.hpp.
References mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::overclusteringFactor, and mlpack::Log::Warn.
const InitialPartitionPolicy& mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::Partitioner | ( | ) | const [inline] |
Get the initial partitioning policy.
Definition at line 166 of file kmeans.hpp.
References mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::partitioner.
InitialPartitionPolicy& mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::Partitioner | ( | ) | [inline] |
Modify the initial partitioning policy.
Definition at line 168 of file kmeans.hpp.
References mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::partitioner.
EmptyClusterPolicy mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::emptyClusterAction [private] |
Instantiated empty cluster policy.
Definition at line 188 of file kmeans.hpp.
Referenced by mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::EmptyClusterAction().
size_t mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::maxIterations [private] |
Maximum number of iterations before giving up.
Definition at line 182 of file kmeans.hpp.
Referenced by mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::MaxIterations().
DistanceMetric mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::metric [private] |
Instantiated distance metric.
Definition at line 184 of file kmeans.hpp.
Referenced by mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::Metric().
double mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::overclusteringFactor [private] |
Factor controlling how many clusters are actually found.
Definition at line 180 of file kmeans.hpp.
Referenced by mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::OverclusteringFactor().
InitialPartitionPolicy mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::partitioner [private] |
Instantiated initial partitioning policy.
Definition at line 186 of file kmeans.hpp.
Referenced by mlpack::kmeans::KMeans< DistanceMetric, InitialPartitionPolicy, EmptyClusterPolicy >::Partitioner().