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Posted to commits@systemds.apache.org by ja...@apache.org on 2020/07/08 19:15:09 UTC

[systemds] branch master updated: [DOC][2/2] Builtin KMeans function example added

This is an automated email from the ASF dual-hosted git repository.

janardhan pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/systemds.git


The following commit(s) were added to refs/heads/master by this push:
     new 7cdb51d  [DOC][2/2] Builtin KMeans function example added
7cdb51d is described below

commit 7cdb51d18ee1a9d7a957f366a71d04ca818bdf91
Author: Janardhan Pulivarthi <j1...@protonmail.com>
AuthorDate: Thu Jun 4 10:18:34 2020 +0530

    [DOC][2/2] Builtin KMeans function example added
    
      * Example to invoke KMeans function
      * Update the KMeans default number of centroids in dml script.
    
    Closes #947.
---
 docs/site/builtins-reference.md | 5 +++++
 scripts/builtin/kmeans.dml      | 2 +-
 2 files changed, 6 insertions(+), 1 deletion(-)

diff --git a/docs/site/builtins-reference.md b/docs/site/builtins-reference.md
index 812245d..c96e5d7 100644
--- a/docs/site/builtins-reference.md
+++ b/docs/site/builtins-reference.md
@@ -435,6 +435,11 @@ kmeans(X = X, k = 20, runs = 10, max_iter = 5000, eps = 0.000001, is_verbose = F
 | String | The mapping of records to centroids |
 | String | The output matrix with the centroids |
 
+### Example
+```r
+X = rand (rows = 3972, cols = 972)
+kmeans(X = X, k = 20, runs = 10, max_iter = 5000, eps = 0.000001, is_verbose = FALSE, avg_sample_size_per_centroid = 50)
+```
 
 ## `lm`-Function
 
diff --git a/scripts/builtin/kmeans.dml b/scripts/builtin/kmeans.dml
index 75e5bc7..6a4d249 100644
--- a/scripts/builtin/kmeans.dml
+++ b/scripts/builtin/kmeans.dml
@@ -43,7 +43,7 @@
 # ----------------------------------------------------------------------------
 
 
-m_kmeans = function(Matrix[Double] X, Integer k = 0, Integer runs = 10, Integer max_iter = 1000,
+m_kmeans = function(Matrix[Double] X, Integer k = 10, Integer runs = 10, Integer max_iter = 1000,
     Double eps = 0.000001, Boolean is_verbose = FALSE, Integer avg_sample_size_per_centroid = 50)
   return (Matrix[Double] C, Matrix[Double] Y)
 {