[Octave-patch-tracker] [patch #10052] [octave forge] (statistics) Add function evalclusters

[anonymous]

URL:
  <https://savannah.gnu.org/patch/?10052>

                 Summary: [octave forge] (statistics) Add function
evalclusters
                 Project: GNU Octave
            Submitted by: None
            Submitted on: Sat 03 Apr 2021 04:12:40 PM UTC
                Category: Forge : new function
                Priority: 5 - Normal
                  Status: None
                 Privacy: Public
             Assigned to: None
        Originator Email: s.guidoni@virgilio.it
             Open/Closed: Open
         Discussion Lock: Any

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Details:

This is a patch to add function "evalclusters" and its related classes.

The function "evalclusters" returns a "ClusterCriterion" object, which is used
to evaluate different clustering solutions.

Example:

>> load fisheriris;
>> eva = evalclusters(meas,"kmeans","calinskiharabasz","KList",[1:6])
eva =

  CalinskiHarabaszEvaluation object with properties:

      ClusteringFunction: kmeans
           CriterionName: CalinskiHarabasz
         CriterionValues: [1x6 double]
              InspectedK: [1x6 double]
                 Missing: [1x150 double]
         NumObservations: [1x1 double]
                OptimalK: [1x1 double]
                OptimalY: [150x1 double]
                       X: [150x4 double]
>> eva.OptimalK
ans = 3
>> figure();
>> eva.plot();


The "CalinskiHarabaszEvaluation" class is a subclass of "ClusterCriterion",
which uses the Calinski-Harabasz criterion to guess the optimal clustering
solution.

The implemented criterions are: "CalinskiHarabasz", "DaviesBouldin", "gap",
"silhouette".

The method "compact", which converts an evaluation object into a compact
evaluation object is not implemented.

For the gap criterion the reference distribution "PCA" is not implemented:
when the reference distribution is set to "PCA", it uses "uniform" instead and
throws a warning. Note: function "princomp", which is used to do a principal
component analysis of some data, is now called "pca" in MATLAB.

I tested most stuff, but not everything. There are many available options and
different combinations of such options to test.




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File Attachments:


-------------------------------------------------------
Date: Sat 03 Apr 2021 04:12:40 PM UTC  Name: evalclusters.diff  Size: 69KiB  
By: None

<http://savannah.gnu.org/patch/download.php?file_id=51182>

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