Answers.Body: <p>The best way to reduce the number of clusters produced by the Markov Clustering Algorithm (MCA) will <strong>depend on the specifics of your data</strong> and <strong>how you want to cluster it</strong>. However, some general tips that may help include:</p>
  <ul>
  <li><p>One way is to <strong>pre-process your data</strong> to remove noise and outliers. This can help to make your data more amenable to clustering and make it more likely that meaningful patterns will emerge.</p>
  </li>
  <li><p>Some methods that may be effective in reducing the number of clusters produced by MCA include <strong>downsampling the dataset</strong>, using a smaller value for the clustering parameter (such as the number of iterations), or using a threshold value to filter out small clusters.</p>
  </li>
  <li><p>Another approach is to play with the MCL parameters, such as the <strong>inflation rate</strong>, to see if that has an effect on the number of clusters produced. try increasing its value, this will lead to fewer, but larger clusters.</p>
  </li>
  <li><p>Use a different <strong>similarity measure</strong>.</p>
  </li>
  <li><p>you could try running MCL multiple times with different <strong>random seeds</strong> to see if that makes a difference.</p>
  </li>
  </ul>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2022-10-17T19:46:59.200Z
Answers.LastActivityDate: 2022-10-17T19:59:20.467Z
Answers.LastEditDate: 2022-10-17T19:59:20.467Z
Answers.UserDisplayName: Faizy
Answers.Body: <p>Depending on the implementation you're using, you can adjust the <em>granularity</em>, which will influence how many clusters you will get.</p>
  <p>See <a href="http://micans.org/mcl/" rel="nofollow noreferrer">this description of MCL</a>.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-09-24T23:07:23.063Z
Answers.Text: Thank you for your answer, you mean I adjust inflation parameter of mcl to get better clusers? Is that what you mean by granularity?
Answers.UserDisplayName: Adnan Hussein
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-09-25T18:26:53.727Z
Answers.Text: No, granularity is not the same as inflation. Are there no other parameter you can adjust?
Answers.UserDisplayName: Oliver Mason
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-09-22T07:40:29.830Z
Answers.LastActivityDate: 2021-09-22T07:40:29.830Z
Answers.UserDisplayName: Oliver Mason
Body: <p>I have used the Markov Clustering Algorithm (MCL) to cluster tweets, based on their similarity. However, I got a too high number of clusters, and most of the clusters have only one tweet. Any suggestions to reduce the number of clusters?</p>
  
Tags: <natural-language-processing><hyper-parameters><clustering><cosine-similarity>
Title: How to reduce the number of clusters produced by the Markov Clustering Algorithm?
UserDisplayName: Adnan Hussein
ThreadText: # How to reduce the number of clusters produced by the Markov Clustering Algorithm?
  
  (Asked by: username_0 on 2021-09-22)
  
  I have used the Markov Clustering Algorithm (MCL) to cluster tweets, based on their similarity. However, I got a too high number of clusters, and most of the clusters have only one tweet. Any suggestions to reduce the number of clusters?
  
  **Tags:** natural-language-processing, hyper-parameters, clustering, cosine-similarity
  
  ---
  
  ## 2 answers
  
  ### Answer by username_1 on 2022-10-17. Score: 0 | Accepted answer
  
  The best way to reduce the number of clusters produced by the Markov Clustering Algorithm (MCA) will **depend on the specifics of your data** and **how you want to cluster it**. However, some general tips that may help include:
  
  * One way is to **pre-process your data** to remove noise and outliers. This can help to make your data more amenable to clustering and make it more likely that meaningful patterns will emerge.
  * Some methods that may be effective in reducing the number of clusters produced by MCA include **downsampling the dataset**, using a smaller value for the clustering parameter (such as the number of iterations), or using a threshold value to filter out small clusters.
  * Another approach is to play with the MCL parameters, such as the **inflation rate**, to see if that has an effect on the number of clusters produced. try increasing its value, this will lead to fewer, but larger clusters.
  * Use a different **similarity measure**.
  * you could try running MCL multiple times with different **random seeds** to see if that makes a difference.
  
  
  ---
  
  ### Answer by username_2 on 2021-09-22. Score: 0
  
  Depending on the implementation you're using, you can adjust the *granularity*, which will influence how many clusters you will get.
  
  See [this description of MCL](http://micans.org/mcl/).
  
  > **Comments:**
  > **username_0**: Thank you for your answer, you mean I adjust inflation parameter of mcl to get better clusers? Is that what you mean by granularity?  
  > **username_2**: No, granularity is not the same as inflation. Are there no other parameter you can adjust?  
  
  ---
  
  