OiO.lk Community platform!

Oio.lk is an excellent forum for developers, providing a wide range of resources, discussions, and support for those in the developer community. Join oio.lk today to connect with like-minded professionals, share insights, and stay updated on the latest trends and technologies in the development field.
  You need to log in or register to access the solved answers to this problem.
  • You have reached the maximum number of guest views allowed
  • Please register below to remove this limitation

Change point detection in a timeseries

  • Thread starter Thread starter Raj
  • Start date Start date
R

Raj

Guest
I have a few questions about using the PELT algorithm for change point detection in the ruptures library.

  1. Optimal Penalty Value for PELT Algorithm

I'm using the Pruned Exact Linear Time (PELT) algorithm in the ruptures library for change point detection. How to choose the optimal penalty value effectively? Currently computing using below formula [2], but it is not working.

Code:
    model = rpt.Pelt(model="l2", 
    min_size=segment,jump=jump_factor).fit(data_np)
    n = len(data)
    sensitivity = 0.5

    penalty_1 = ((0.25*n)**(1-sensitivity)) * ((2 * np.log(n))) # mean/std case
    penalty_2 = 6**(2-2*sensitivity) # trend case
   
    change_indices_1 = model.predict(pen=penalty_1)
    change_indices_2 = model.predict(pen=penalty_2)
  1. Handling Gradual Changes with PELT Algorithm

I've noticed that gradual changes in the data can lead to multiple change points being detected during the transition period. How can I adjust the PELT algorithm in ruptures to handle gradual changes and avoid detecting unnecessary change points?

changepoint(ruptures is currently capturing

actual changepoints it should capture (in vertical lines)

  1. Improving Changepoint Detection for Standard Deviation Changes

I've observed that the PELT algorithm in ruptures struggles to detect changes in the standard deviation of the data. How can I improve the detection of change points in the ruptures library when there are changes in the standard deviation?

eg-1: changepoints detected in case of standard deviation using ruptures

eg-2: changepoints detected in case of standard deviation using ruptures

I read these articles on change point detection using PELT, 1 and 2, but I'm still unsure about how to address these issues.
<p>I have a few questions about using the PELT algorithm for change point detection in the ruptures library.</p>
<ol>
<li><strong>Optimal Penalty Value for PELT Algorithm</strong></li>
</ol>
<p>I'm using the Pruned Exact Linear Time (PELT) algorithm in the ruptures library for change point detection. How to choose the optimal penalty value effectively?
Currently computing using below formula [2], but it is not working.</p>
<pre><code> model = rpt.Pelt(model="l2",
min_size=segment,jump=jump_factor).fit(data_np)
n = len(data)
sensitivity = 0.5

penalty_1 = ((0.25*n)**(1-sensitivity)) * ((2 * np.log(n))) # mean/std case
penalty_2 = 6**(2-2*sensitivity) # trend case

change_indices_1 = model.predict(pen=penalty_1)
change_indices_2 = model.predict(pen=penalty_2)
</code></pre>
<ol start="2">
<li><strong>Handling Gradual Changes with PELT Algorithm</strong></li>
</ol>
<p>I've noticed that gradual changes in the data can lead to multiple change points being detected during the transition period. How can I adjust the PELT algorithm in ruptures to handle gradual changes and avoid detecting unnecessary change points?</p>
<p><a href="https://i.sstatic.net/pd3qzJfg.png" rel="nofollow noreferrer">changepoint(ruptures is currently capturing</a></p>
<p><a href="https://i.sstatic.net/9Lhl3GKN.png" rel="nofollow noreferrer">actual changepoints it should capture (in vertical lines)</a></p>
<ol start="3">
<li><strong>Improving Changepoint Detection for Standard Deviation Changes</strong></li>
</ol>
<p>I've observed that the PELT algorithm in ruptures struggles to detect changes in the standard deviation of the data. How can I improve the detection of change points in the ruptures library when there are changes in the standard deviation?</p>
<p><a href="https://i.sstatic.net/EfKOTfZP.png" rel="nofollow noreferrer">eg-1: changepoints detected in case of standard deviation using ruptures</a></p>
<p><a href="https://i.sstatic.net/JIzc6e2C.png" rel="nofollow noreferrer">eg-2: changepoints detected in case of standard deviation using ruptures</a></p>
<p>I read these articles on change point detection using PELT,
<a href="https://stackoverflow.com/questions/71920414/change-point-detection-pelt">1</a> and
<a href="https://pro.arcgis.com/en/pro-app/l...n-mining/how-change-point-detection-works.htm" rel="nofollow noreferrer">2</a>, but I'm still unsure about how to address these issues.</p>
 

Latest posts

Top