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    • Update kmeans authored by Dean Samuel Schmitz's avatar Dean Samuel Schmitz
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    PrologMethods/Clustering/kmeans.md
    View page @ 816be71f
    ...@@ -4,23 +4,25 @@ An implementation of several strategies for efficient k-means clustering. Given ...@@ -4,23 +4,25 @@ An implementation of several strategies for efficient k-means clustering. Given
    # Available Predicates # Available Predicates
    * [naiveKMeans/12](/PrologMethods/Clustering/kmeans#naivekmeans12) * [naiveKMeans/9](/PrologMethods/Clustering/kmeans#naivekmeans9)
    * [dualTreeKMeans/12](/PrologMethods/Clustering/kmeans#dualtreekmeans12) * [dualTreeKMeans/9](/PrologMethods/Clustering/kmeans#dualtreekmeans9)
    * [elkanKMeans/12](/PrologMethods/Clustering/kmeans#elkankmeans12) * [elkanKMeans/9](/PrologMethods/Clustering/kmeans#elkankmeans9)
    * [hamerlyKMeans/12](/PrologMethods/Clustering/kmeans#hamerlykmeans12) * [hamerlyKMeans/9](/PrologMethods/Clustering/kmeans#hamerlykmeans12)
    * [pellegMooreKMeans/12](/PrologMethods/Clustering/kmeans#pellegmoorekmeans12) * [pellegMooreKMeans/9](/PrologMethods/Clustering/kmeans#pellegmoorekmeans9)
    --- ---
    [links/resources](/PrologMethods/Clustering/kmeans#connected-linksresources) [links/resources](/PrologMethods/Clustering/kmeans#connected-linksresources)
    ## **_naiveKMeans/12_** ## **_naiveKMeans/9_**
    Runs kmeans with naive as the algorithm for the Lloyd iteration. Runs kmeans with naive as the algorithm for the Lloyd iteration.
    ```prolog ```prolog
    %% part of the predicate definition %% part of the predicate definition
    naiveKMeans( +integer, +integer, +integer, naiveKMeans( +integer,
    +string,
    +string,
    +pointer(float_array), +integer, +integer, +pointer(float_array), +integer, +integer,
    +integer, +integer,
    -pointer(float_array), -integer, -pointer(float_array), -integer,
    ...@@ -31,8 +33,8 @@ naiveKMeans( +integer, +integer, +integer, ...@@ -31,8 +33,8 @@ naiveKMeans( +integer, +integer, +integer,
    | Name | Type | Description | Default | | Name | Type | Description | Default |
    |------|------|-------------|---------| |------|------|-------------|---------|
    | maxIterations | +integer | Maximum number of iterations before k-means terminates. | 1000 | | maxIterations | +integer | Maximum number of iterations before k-means terminates. | 1000 |
    | initialPartition | +string | Sets the initialPartitionPolicy : "SampleInitialzation", "RandomPartition" | SampleInitialzation | | initialPartition | +string | Sets the initialPartitionPolicy : "sampleInitialization", "randomPartition" | sampleInitialzation |
    | emptyCluster | +string | Sets the emptyClusterPolicy: "MaxVarianceNewCluster", "KillEmptyCluster", "AllowEmptyCluster" | AllowEmptyCluster | | emptyCluster | +string | Sets the emptyClusterPolicy: "maxVarianceNewCluster", "killEmptyCluster", "allowEmptyCluster" | allowEmptyCluster |
    | data | +matrix | Input dataset to perform clustering on. | - | | data | +matrix | Input dataset to perform clustering on. | - |
    | clusters | +integer | Number of clusters to find (0 autodetects from initial centroids). | 0 | | clusters | +integer | Number of clusters to find (0 autodetects from initial centroids). | 0 |
    | assignments | -vector | Vector to store cluster assignments in. | - | | assignments | -vector | Vector to store cluster assignments in. | - |
    ...@@ -40,13 +42,15 @@ naiveKMeans( +integer, +integer, +integer, ...@@ -40,13 +42,15 @@ naiveKMeans( +integer, +integer, +integer,
    --- ---
    ## **_dualTreeKMeans/12_** ## **_dualTreeKMeans/9_**
    Runs kmeans with dualtree as the algorithm for the Lloyd iteration. Runs kmeans with dualtree as the algorithm for the Lloyd iteration.
    ```prolog ```prolog
    %% part of the predicate definition %% part of the predicate definition
    dualTreeKMeans( +integer, +integer, +integer, dualTreeKMeans( +integer,
    +string,
    +string,
    +pointer(float_array), +integer, +integer, +pointer(float_array), +integer, +integer,
    +integer, +integer,
    -pointer(float_array), -integer, -pointer(float_array), -integer,
    ...@@ -57,8 +61,8 @@ dualTreeKMeans( +integer, +integer, +integer, ...@@ -57,8 +61,8 @@ dualTreeKMeans( +integer, +integer, +integer,
    | Name | Type | Description | Default | | Name | Type | Description | Default |
    |------|------|-------------|---------| |------|------|-------------|---------|
    | maxIterations | +integer | Maximum number of iterations before k-means terminates. | 1000 | | maxIterations | +integer | Maximum number of iterations before k-means terminates. | 1000 |
    | initialPartition | +string | Sets the initialPartitionPolicy : "SampleInitialzation", "RandomPartition" | SampleInitialzation | | initialPartition | +string | Sets the initialPartitionPolicy : "sampleInitialization", "randomPartition" | sampleInitialzation |
    | emptyCluster | +string | Sets the emptyClusterPolicy: "MaxVarianceNewCluster", "KillEmptyCluster", "AllowEmptyCluster" | AllowEmptyCluster | | emptyCluster | +string | Sets the emptyClusterPolicy: "maxVarianceNewCluster", "killEmptyCluster", "allowEmptyCluster" | allowEmptyCluster |
    | data | +matrix | Input dataset to perform clustering on. | - | | data | +matrix | Input dataset to perform clustering on. | - |
    | clusters | +integer | Number of clusters to find (0 autodetects from initial centroids). | 0 | | clusters | +integer | Number of clusters to find (0 autodetects from initial centroids). | 0 |
    | assignments | -vector | Vector to store cluster assignments in. | - | | assignments | -vector | Vector to store cluster assignments in. | - |
    ...@@ -66,13 +70,15 @@ dualTreeKMeans( +integer, +integer, +integer, ...@@ -66,13 +70,15 @@ dualTreeKMeans( +integer, +integer, +integer,
    --- ---
    ## **_elkanKMeans/12_** ## **_elkanKMeans/9_**
    Runs kmeans with elkan as the algorithm for the Lloyd iteration. Runs kmeans with elkan as the algorithm for the Lloyd iteration.
    ```prolog ```prolog
    %% part of the predicate definition %% part of the predicate definition
    elkanKMeans( +integer, +integer, +integer, elkanKMeans( +integer,
    +string,
    +string,
    +pointer(float_array), +integer, +integer, +pointer(float_array), +integer, +integer,
    +integer, +integer,
    -pointer(float_array), -integer, -pointer(float_array), -integer,
    ...@@ -83,8 +89,8 @@ elkanKMeans( +integer, +integer, +integer, ...@@ -83,8 +89,8 @@ elkanKMeans( +integer, +integer, +integer,
    | Name | Type | Description | Default | | Name | Type | Description | Default |
    |------|------|-------------|---------| |------|------|-------------|---------|
    | maxIterations | +integer | Maximum number of iterations before k-means terminates. | 1000 | | maxIterations | +integer | Maximum number of iterations before k-means terminates. | 1000 |
    | initialPartition | +string | Sets the initialPartitionPolicy : "SampleInitialzation", "RandomPartition" | SampleInitialzation | | initialPartition | +string | Sets the initialPartitionPolicy : "sampleInitialization", "randomPartition" | sampleInitialzation |
    | emptyCluster | +string | Sets the emptyClusterPolicy: "MaxVarianceNewCluster", "KillEmptyCluster", "AllowEmptyCluster" | AllowEmptyCluster | | emptyCluster | +string | Sets the emptyClusterPolicy: "maxVarianceNewCluster", "killEmptyCluster", "allowEmptyCluster" | allowEmptyCluster |
    | data | +matrix | Input dataset to perform clustering on. | - | | data | +matrix | Input dataset to perform clustering on. | - |
    | clusters | +integer | Number of clusters to find (0 autodetects from initial centroids). | 0 | | clusters | +integer | Number of clusters to find (0 autodetects from initial centroids). | 0 |
    | assignments | -vector | Vector to store cluster assignments in. | - | | assignments | -vector | Vector to store cluster assignments in. | - |
    ...@@ -92,13 +98,15 @@ elkanKMeans( +integer, +integer, +integer, ...@@ -92,13 +98,15 @@ elkanKMeans( +integer, +integer, +integer,
    --- ---
    ## **_hamerlyKMeans/12_** ## **_hamerlyKMeans/9_**
    Runs kmeans with hamerly as the algorithm for the Lloyd iteration. Runs kmeans with hamerly as the algorithm for the Lloyd iteration.
    ```prolog ```prolog
    %% part of the predicate definition %% part of the predicate definition
    hamerlyKMeans( +integer, +integer, +integer, hamerlyKMeans( +integer,
    +string,
    +string,
    +pointer(float_array), +integer, +integer, +pointer(float_array), +integer, +integer,
    +integer, +integer,
    -pointer(float_array), -integer, -pointer(float_array), -integer,
    ...@@ -109,8 +117,8 @@ hamerlyKMeans( +integer, +integer, +integer, ...@@ -109,8 +117,8 @@ hamerlyKMeans( +integer, +integer, +integer,
    | Name | Type | Description | Default | | Name | Type | Description | Default |
    |------|------|-------------|---------| |------|------|-------------|---------|
    | maxIterations | +integer | Maximum number of iterations before k-means terminates. | 1000 | | maxIterations | +integer | Maximum number of iterations before k-means terminates. | 1000 |
    | initialPartition | +string | Sets the initialPartitionPolicy : "SampleInitialzation", "RandomPartition" | SampleInitialzation | | initialPartition | +string | Sets the initialPartitionPolicy : "sampleInitialization", "randomPartition" | sampleInitialzation |
    | emptyCluster | +string | Sets the emptyClusterPolicy: "MaxVarianceNewCluster", "KillEmptyCluster", "AllowEmptyCluster" | AllowEmptyCluster | | emptyCluster | +string | Sets the emptyClusterPolicy: "maxVarianceNewCluster", "killEmptyCluster", "allowEmptyCluster" | allowEmptyCluster |
    | data | +matrix | Input dataset to perform clustering on. | - | | data | +matrix | Input dataset to perform clustering on. | - |
    | clusters | +integer | Number of clusters to find (0 autodetects from initial centroids). | 0 | | clusters | +integer | Number of clusters to find (0 autodetects from initial centroids). | 0 |
    | assignments | -vector | Vector to store cluster assignments in. | - | | assignments | -vector | Vector to store cluster assignments in. | - |
    ...@@ -118,13 +126,15 @@ hamerlyKMeans( +integer, +integer, +integer, ...@@ -118,13 +126,15 @@ hamerlyKMeans( +integer, +integer, +integer,
    --- ---
    ## **_pellegMooreKMeans/12\]_** ## **_pellegMooreKMeans/9_**
    Runs kmeans with pelleg morre as the algorithm for the Lloyd iteration. Runs kmeans with pelleg morre as the algorithm for the Lloyd iteration.
    ```prolog ```prolog
    %% part of the predicate definition %% part of the predicate definition
    pellegMooreKMeans( +integer, +integer, +integer, pellegMooreKMeans( +integer,
    +string,
    +string,
    +pointer(float_array), +integer, +integer, +pointer(float_array), +integer, +integer,
    +integer, +integer,
    -pointer(float_array), -integer, -pointer(float_array), -integer,
    ...@@ -135,8 +145,8 @@ pellegMooreKMeans( +integer, +integer, +integer, ...@@ -135,8 +145,8 @@ pellegMooreKMeans( +integer, +integer, +integer,
    | Name | Type | Description | Default | | Name | Type | Description | Default |
    |------|------|-------------|---------| |------|------|-------------|---------|
    | maxIterations | +integer | Maximum number of iterations before k-means terminates. | 1000 | | maxIterations | +integer | Maximum number of iterations before k-means terminates. | 1000 |
    | initialPartition | +string | Sets the initialPartitionPolicy : "SampleInitialzation", "RandomPartition" | SampleInitialzation | | initialPartition | +string | Sets the initialPartitionPolicy : "sampleInitialization", "randomPartition" | sampleInitialzation |
    | emptyCluster | +string | Sets the emptyClusterPolicy: "MaxVarianceNewCluster", "KillEmptyCluster", "AllowEmptyCluster" | AllowEmptyCluster | | emptyCluster | +string | Sets the emptyClusterPolicy: "maxVarianceNewCluster", "killEmptyCluster", "allowEmptyCluster" | allowEmptyCluster |
    | data | +matrix | Input dataset to perform clustering on. | - | | data | +matrix | Input dataset to perform clustering on. | - |
    | clusters | +integer | Number of clusters to find (0 autodetects from initial centroids). | 0 | | clusters | +integer | Number of clusters to find (0 autodetects from initial centroids). | 0 |
    | assignments | -vector | Vector to store cluster assignments in. | - | | assignments | -vector | Vector to store cluster assignments in. | - |
    ......