Answers.Body: <p>there is an -init option for that </p>
  
  <p><em>Initialization method to use.
    0 = random, 1 = k-means++, 2 = canopy, 3 = farthest first.
    (default = 0)</em>
  kmeans++ will give you an option for you to initialize centres.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2018-06-02T13:29:06.447Z
Answers.LastActivityDate: 2018-06-02T13:29:06.447Z
Answers.UserDisplayName: thecomplexitytheorist
Body: <p>Is there a way in the WEKA explorer to manually select the initial centres when using SimpleKMeans clustering?</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-05-31T16:38:57.007Z
Comments.Text: why would you want to choost your centres "manually" , they are assigned at random locations and they are re-assigned after each iteration of the clustering algorithm , so there is no point in "manually" initializing the centres.
Comments.UserDisplayName: thecomplexitytheorist
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2018-06-02T12:54:17.880Z
Comments.Text: I understand that is how they are usually selected. However, I was told I had to set the initial centres for an assignment and could not find a way to do so.
Comments.UserDisplayName: Hogg44
Tags: <machine-learning>
Title: WEKA - SimpleKMeans - Manually choose intitial centres
UserDisplayName: Hogg44
ThreadText: # WEKA - SimpleKMeans - Manually choose intitial centres
  
  (Asked by: username_0 on 2018-05-26)
  
  Is there a way in the WEKA explorer to manually select the initial centres when using SimpleKMeans clustering?
  
  **Tags:** machine-learning
  > **Comments:**
  > **username_1**: why would you want to choost your centres "manually" , they are assigned at random locations and they are re-assigned after each iteration of the clustering algorithm , so there is no point in "manually" initializing the centres.  
  > **username_0**: I understand that is how they are usually selected. However, I was told I had to set the initial centres for an assignment and could not find a way to do so.  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_1 on 2018-06-02. Score: 1
  
  there is an -init option for that
  
  *Initialization method to use.
  0 = random, 1 = k-means++, 2 = canopy, 3 = farthest first.
  (default = 0)*
  kmeans++ will give you an option for you to initialize centres.
  
  
  ---
  
  